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Mocci G, Sukhavasi K, Örd T, Bankier S, Singha P, Arasu UT, Agbabiaje OO, Mäkinen P, Ma L, Hodonsky CJ, Aherrahrou R, Muhl L, Liu J, Gustafsson S, Byandelger B, Wang Y, Koplev S, Lendahl U, Owens GK, Leeper NJ, Pasterkamp G, Vanlandewijck M, Michoel T, Ruusalepp A, Hao K, Ylä-Herttuala S, Väli M, Järve H, Mokry M, Civelek M, Miller CJ, Kovacic JC, Kaikkonen MU, Betsholtz C, Björkegren JLM. Single-Cell Gene-Regulatory Networks of Advanced Symptomatic Atherosclerosis. Circ Res 2024; 134:1405-1423. [PMID: 38639096 DOI: 10.1161/circresaha.123.323184] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/04/2023] [Accepted: 04/04/2024] [Indexed: 04/20/2024]
Abstract
BACKGROUND While our understanding of the single-cell gene expression patterns underlying the transformation of vascular cell types during the progression of atherosclerosis is rapidly improving, the clinical and pathophysiological relevance of these changes remains poorly understood. METHODS Single-cell RNA sequencing data generated with SmartSeq2 (≈8000 genes/cell) in 16 588 single cells isolated during atherosclerosis progression in Ldlr-/-Apob100/100 mice with human-like plasma lipoproteins and from humans with asymptomatic and symptomatic carotid plaques was clustered into multiple subtypes. For clinical and pathophysiological context, the advanced-stage and symptomatic subtype clusters were integrated with 135 tissue-specific (atherosclerotic aortic wall, mammary artery, liver, skeletal muscle, and visceral and subcutaneous, fat) gene-regulatory networks (GRNs) inferred from 600 coronary artery disease patients in the STARNET (Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task) study. RESULTS Advanced stages of atherosclerosis progression and symptomatic carotid plaques were largely characterized by 3 smooth muscle cells (SMCs), and 3 macrophage subtype clusters with extracellular matrix organization/osteogenic (SMC), and M1-type proinflammatory/Trem2-high lipid-associated (macrophage) phenotypes. Integrative analysis of these 6 clusters with STARNET revealed significant enrichments of 3 arterial wall GRNs: GRN33 (macrophage), GRN39 (SMC), and GRN122 (macrophage) with major contributions to coronary artery disease heritability and strong associations with clinical scores of coronary atherosclerosis severity. The presence and pathophysiological relevance of GRN39 were verified in 5 independent RNAseq data sets obtained from the human coronary and aortic artery, and primary SMCs and by targeting its top-key drivers, FRZB and ALCAM in cultured human coronary artery SMCs. CONCLUSIONS By identifying and integrating the most gene-rich single-cell subclusters of atherosclerosis to date with a coronary artery disease framework of GRNs, GRN39 was identified and independently validated as being critical for the transformation of contractile SMCs into an osteogenic phenotype promoting advanced, symptomatic atherosclerosis.
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MESH Headings
- Humans
- Single-Cell Analysis
- Animals
- Gene Regulatory Networks
- Atherosclerosis/genetics
- Atherosclerosis/metabolism
- Atherosclerosis/pathology
- Mice
- Myocytes, Smooth Muscle/metabolism
- Myocytes, Smooth Muscle/pathology
- Male
- Plaque, Atherosclerotic
- Disease Progression
- Female
- Macrophages/metabolism
- Macrophages/pathology
- Mice, Knockout
- Receptors, LDL/genetics
- Receptors, LDL/metabolism
- Mice, Inbred C57BL
- Muscle, Smooth, Vascular/metabolism
- Muscle, Smooth, Vascular/pathology
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Affiliation(s)
- Giuseppe Mocci
- Department of Medicine (Huddinge), Karolinska Institutet, Sweden (G.M., L. Muhl, J.L., S.G., B.B., U.L., M.V., C.B., J.L.M.B.)
| | - Katyayani Sukhavasi
- Department of Cardiac Surgery and The Heart Clinic, Tartu University Hospital and Department of Cardiology, Institute of Clinical Medicine, Tartu University, Estonia (K.S., A.R., H.J.)
| | - Tiit Örd
- A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio (T.O., P.S., U.T.A., O.O.A., P.M., S.Y.-H., M.U.K.)
| | - Sean Bankier
- Computational Biology Unit, Department of Informatics, University of Bergen, Norway (S.B., T.M.)
| | - Prosanta Singha
- A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio (T.O., P.S., U.T.A., O.O.A., P.M., S.Y.-H., M.U.K.)
| | - Uma Thanigai Arasu
- A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio (T.O., P.S., U.T.A., O.O.A., P.M., S.Y.-H., M.U.K.)
| | - Olayinka Oluwasegun Agbabiaje
- A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio (T.O., P.S., U.T.A., O.O.A., P.M., S.Y.-H., M.U.K.)
| | - Petri Mäkinen
- A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio (T.O., P.S., U.T.A., O.O.A., P.M., S.Y.-H., M.U.K.)
| | - Lijiang Ma
- Department of Genetics and Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York (L. Ma, S.K., K.H., J.L.M.B.)
| | - Chani J Hodonsky
- Robert M. Berne Cardiovascular Research Center (C.J.H., G.K.O., C.J.M.), University of Virginia, Charlottesville
- Center for Public Health Genomics (C.J.H., R.A., M.C.), University of Virginia, Charlottesville
| | - Redouane Aherrahrou
- Center for Public Health Genomics (C.J.H., R.A., M.C.), University of Virginia, Charlottesville
- Department of Biomedical Engineering (R.A., M.C.), University of Virginia, Charlottesville
| | - Lars Muhl
- Department of Medicine (Huddinge), Karolinska Institutet, Sweden (G.M., L. Muhl, J.L., S.G., B.B., U.L., M.V., C.B., J.L.M.B.)
| | - Jianping Liu
- Department of Medicine (Huddinge), Karolinska Institutet, Sweden (G.M., L. Muhl, J.L., S.G., B.B., U.L., M.V., C.B., J.L.M.B.)
| | - Sonja Gustafsson
- Department of Medicine (Huddinge), Karolinska Institutet, Sweden (G.M., L. Muhl, J.L., S.G., B.B., U.L., M.V., C.B., J.L.M.B.)
| | - Byambajav Byandelger
- Department of Medicine (Huddinge), Karolinska Institutet, Sweden (G.M., L. Muhl, J.L., S.G., B.B., U.L., M.V., C.B., J.L.M.B.)
| | - Ying Wang
- Division of Vascular Surgery, Department of Surgery, Stanford University School of Medicine, CA (Y.W., N.J.L.)
- Stanford Cardiovascular Institute, Stanford University, CA (Y.W., N.J.L.)
| | - Simon Koplev
- Department of Genetics and Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York (L. Ma, S.K., K.H., J.L.M.B.)
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, United Kingdom (S.K.)
| | - Urban Lendahl
- Department of Medicine (Huddinge), Karolinska Institutet, Sweden (G.M., L. Muhl, J.L., S.G., B.B., U.L., M.V., C.B., J.L.M.B.)
| | - Gary K Owens
- Robert M. Berne Cardiovascular Research Center (C.J.H., G.K.O., C.J.M.), University of Virginia, Charlottesville
| | - Nicholas J Leeper
- Division of Vascular Surgery, Department of Surgery, Stanford University School of Medicine, CA (Y.W., N.J.L.)
- Stanford Cardiovascular Institute, Stanford University, CA (Y.W., N.J.L.)
| | - Gerard Pasterkamp
- Laboratory of Experimental Cardiology (G.P., M.M.), University Medical Center Utrecht, the Netherlands
- Central Diagnostics Laboratory (G.P., M.M.), University Medical Center Utrecht, the Netherlands
| | - Michael Vanlandewijck
- Department of Medicine (Huddinge), Karolinska Institutet, Sweden (G.M., L. Muhl, J.L., S.G., B.B., U.L., M.V., C.B., J.L.M.B.)
| | - Tom Michoel
- Computational Biology Unit, Department of Informatics, University of Bergen, Norway (S.B., T.M.)
| | - Arno Ruusalepp
- Department of Cardiac Surgery and The Heart Clinic, Tartu University Hospital and Department of Cardiology, Institute of Clinical Medicine, Tartu University, Estonia (K.S., A.R., H.J.)
| | - Ke Hao
- Department of Genetics and Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York (L. Ma, S.K., K.H., J.L.M.B.)
| | - Seppo Ylä-Herttuala
- A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio (T.O., P.S., U.T.A., O.O.A., P.M., S.Y.-H., M.U.K.)
| | - Marika Väli
- Department of Immunology, Genetics, and Pathology, Rudbeck Laboratory, Uppsala University, Sweden (M.V., C.B.)
- Department of Pathological anatomy and Forensic medicine, Institute of Biomedicine and Translational Medicine, University of Tartu, Estonia (M.V.)
| | - Heli Järve
- Department of Cardiac Surgery and The Heart Clinic, Tartu University Hospital and Department of Cardiology, Institute of Clinical Medicine, Tartu University, Estonia (K.S., A.R., H.J.)
| | - Michal Mokry
- A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio (T.O., P.S., U.T.A., O.O.A., P.M., S.Y.-H., M.U.K.)
- Laboratory of Experimental Cardiology (G.P., M.M.), University Medical Center Utrecht, the Netherlands
| | - Mete Civelek
- Center for Public Health Genomics (C.J.H., R.A., M.C.), University of Virginia, Charlottesville
- Department of Biomedical Engineering (R.A., M.C.), University of Virginia, Charlottesville
| | - Clint J Miller
- Robert M. Berne Cardiovascular Research Center (C.J.H., G.K.O., C.J.M.), University of Virginia, Charlottesville
| | - Jason C Kovacic
- Cardiovascular Research Institute, Icahn School of Medicine at Mount Sinai, New York (J.C.K.)
- Victor Chang Cardiac Research Institute, Darlinghurst, Australia (J.C.K.)
- St. Vincent's Clinical School, University of NSW, Sydney, Australia (J.C.K.)
| | - Minna U Kaikkonen
- A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio (T.O., P.S., U.T.A., O.O.A., P.M., S.Y.-H., M.U.K.)
| | - Christer Betsholtz
- Department of Medicine (Huddinge), Karolinska Institutet, Sweden (G.M., L. Muhl, J.L., S.G., B.B., U.L., M.V., C.B., J.L.M.B.)
- Department of Immunology, Genetics, and Pathology, Rudbeck Laboratory, Uppsala University, Sweden (M.V., C.B.)
| | - Johan L M Björkegren
- Department of Medicine (Huddinge), Karolinska Institutet, Sweden (G.M., L. Muhl, J.L., S.G., B.B., U.L., M.V., C.B., J.L.M.B.)
- Department of Genetics and Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York (L. Ma, S.K., K.H., J.L.M.B.)
- Clinical Gene Networks AB, Stockholm, Sweden (J.L.M.B.)
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2
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Wu X, Zhang H. Omics Approaches Unveiling the Biology of Human Atherosclerotic Plaques. The American Journal of Pathology 2024; 194:482-498. [PMID: 38280419 PMCID: PMC10988765 DOI: 10.1016/j.ajpath.2023.12.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/15/2023] [Revised: 12/16/2023] [Accepted: 12/20/2023] [Indexed: 01/29/2024]
Abstract
Atherosclerosis is a chronic inflammatory disease of the arterial wall, characterized by the buildup of plaques with the accumulation and transformation of lipids, immune cells, vascular smooth muscle cells, and necrotic cell debris. Plaques with collagen-poor thin fibrous caps infiltrated by macrophages and lymphocytes are considered unstable because they are at the greatest risk of rupture and clinical events. However, the current histologic definition of plaque types may not fully capture the complex molecular nature of atherosclerotic plaque biology and the underlying mechanisms contributing to plaque progression, rupture, and erosion. The advances in omics technologies have changed the understanding of atherosclerosis plaque biology, offering new possibilities to improve risk prediction and discover novel therapeutic targets. Genomic studies have shed light on the genetic predisposition to atherosclerosis, and integrative genomic analyses expedite the translation of genomic discoveries. Transcriptomic, proteomic, metabolomic, and lipidomic studies have refined the understanding of the molecular signature of atherosclerotic plaques, aiding in data-driven hypothesis generation for mechanistic studies and offering new prospects for biomarker discovery. Furthermore, advancements in single-cell technologies and emerging spatial analysis techniques have unveiled the heterogeneity and plasticity of plaque cells. This review discusses key omics-based discoveries that have advanced the understanding of human atherosclerotic plaque biology, focusing on insights derived from omics profiling of human atherosclerotic vascular specimens.
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Affiliation(s)
- Xun Wu
- Cardiometabolic Genomics Program, Division of Cardiology, Department of Medicine, Columbia University Irving Medical Center, New York, New York
| | - Hanrui Zhang
- Cardiometabolic Genomics Program, Division of Cardiology, Department of Medicine, Columbia University Irving Medical Center, New York, New York.
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3
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Votava JA, John SV, Li Z, Chen S, Fan J, Parks BW. Mining cholesterol genes from thousands of mouse livers identifies aldolase C as a regulator of cholesterol biosynthesis. J Lipid Res 2024; 65:100525. [PMID: 38417553 PMCID: PMC10965479 DOI: 10.1016/j.jlr.2024.100525] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Revised: 02/12/2024] [Accepted: 02/16/2024] [Indexed: 03/01/2024] Open
Abstract
The availability of genome-wide transcriptomic and proteomic datasets is ever-increasing and often not used beyond initial publication. Here, we applied module-based coexpression network analysis to a comprehensive catalog of 35 mouse genome-wide liver expression datasets (encompassing more than 3800 mice) with the goal of identifying and validating unknown genes involved in cholesterol metabolism. From these 35 datasets, we identified a conserved module of genes enriched with cholesterol biosynthetic genes. Using a systematic approach across the 35 datasets, we identified three genes (Rdh11, Echdc1, and Aldoc) with no known role in cholesterol metabolism. We then performed functional validation studies and show that each gene is capable of regulating cholesterol metabolism. For the glycolytic gene, Aldoc, we demonstrate that it contributes to de novo cholesterol biosynthesis and regulates cholesterol and triglyceride levels in mice. As Aldoc is located within a genome-wide significant genome-wide association studies locus for human plasma cholesterol levels, our studies establish Aldoc as a causal gene within this locus. Through our work, we develop a framework for leveraging mouse genome-wide liver datasets for identifying and validating genes involved in cholesterol metabolism.
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Affiliation(s)
- James A Votava
- Department of Nutritional Sciences, University of Wisconsin-Madison, Madison, WI, USA
| | | | - Zhonggang Li
- Department of Nutritional Sciences, University of Wisconsin-Madison, Madison, WI, USA
| | - Shuyang Chen
- Department of Nutritional Sciences, University of Wisconsin-Madison, Madison, WI, USA
| | - Jing Fan
- Department of Nutritional Sciences, University of Wisconsin-Madison, Madison, WI, USA; Morgridge Institute for Research, Madison, WI, USA
| | - Brian W Parks
- Department of Nutritional Sciences, University of Wisconsin-Madison, Madison, WI, USA.
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4
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Zhou M, Tamburini I, Van C, Molendijk J, Nguyen CM, Chang IYY, Johnson C, Velez LM, Cheon Y, Yeo R, Bae H, Le J, Larson N, Pulido R, Nascimento-Filho CHV, Jang C, Marazzi I, Justice J, Pannunzio N, Hevener AL, Sparks L, Kershaw EE, Nicholas D, Parker BL, Masri S, Seldin MM. Leveraging inter-individual transcriptional correlation structure to infer discrete signaling mechanisms across metabolic tissues. eLife 2024; 12:RP88863. [PMID: 38224289 PMCID: PMC10945578 DOI: 10.7554/elife.88863] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2024] Open
Abstract
Inter-organ communication is a vital process to maintain physiologic homeostasis, and its dysregulation contributes to many human diseases. Given that circulating bioactive factors are stable in serum, occur naturally, and are easily assayed from blood, they present obvious focal molecules for therapeutic intervention and biomarker development. Recently, studies have shown that secreted proteins mediating inter-tissue signaling could be identified by 'brute force' surveys of all genes within RNA-sequencing measures across tissues within a population. Expanding on this intuition, we reasoned that parallel strategies could be used to understand how individual genes mediate signaling across metabolic tissues through correlative analyses of gene variation between individuals. Thus, comparison of quantitative levels of gene expression relationships between organs in a population could aid in understanding cross-organ signaling. Here, we surveyed gene-gene correlation structure across 18 metabolic tissues in 310 human individuals and 7 tissues in 103 diverse strains of mice fed a normal chow or high-fat/high-sucrose (HFHS) diet. Variation of genes such as FGF21, ADIPOQ, GCG, and IL6 showed enrichments which recapitulate experimental observations. Further, similar analyses were applied to explore both within-tissue signaling mechanisms (liver PCSK9) and genes encoding enzymes producing metabolites (adipose PNPLA2), where inter-individual correlation structure aligned with known roles for these critical metabolic pathways. Examination of sex hormone receptor correlations in mice highlighted the difference of tissue-specific variation in relationships with metabolic traits. We refer to this resource as gene-derived correlations across tissues (GD-CAT) where all tools and data are built into a web portal enabling users to perform these analyses without a single line of code (gdcat.org). This resource enables querying of any gene in any tissue to find correlated patterns of genes, cell types, pathways, and network architectures across metabolic organs.
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Affiliation(s)
- Mingqi Zhou
- Department of Biological Chemistry, UC IrvineIrvineUnited States
- Center for Epigenetics and Metabolism, UC IrvineIrvineUnited States
| | - Ian Tamburini
- Department of Biological Chemistry, UC IrvineIrvineUnited States
- Center for Epigenetics and Metabolism, UC IrvineIrvineUnited States
| | - Cassandra Van
- Center for Epigenetics and Metabolism, UC IrvineIrvineUnited States
| | - Jeffrey Molendijk
- Department of Anatomy and Physiology, University of MelbourneMelbourneAustralia
| | - Christy M Nguyen
- Department of Biological Chemistry, UC IrvineIrvineUnited States
- Center for Epigenetics and Metabolism, UC IrvineIrvineUnited States
| | | | - Casey Johnson
- Department of Biological Chemistry, UC IrvineIrvineUnited States
- Center for Epigenetics and Metabolism, UC IrvineIrvineUnited States
| | - Leandro M Velez
- Department of Biological Chemistry, UC IrvineIrvineUnited States
- Center for Epigenetics and Metabolism, UC IrvineIrvineUnited States
| | - Youngseo Cheon
- Department of Biological Chemistry, UC IrvineIrvineUnited States
- Center for Epigenetics and Metabolism, UC IrvineIrvineUnited States
| | - Reichelle Yeo
- Translational Research Institute, AdventHealthOrlandoUnited States
| | - Hosung Bae
- Department of Biological Chemistry, UC IrvineIrvineUnited States
- Center for Epigenetics and Metabolism, UC IrvineIrvineUnited States
| | - Johnny Le
- Department of Biological Chemistry, UC IrvineIrvineUnited States
- Center for Epigenetics and Metabolism, UC IrvineIrvineUnited States
| | - Natalie Larson
- Department of Biological Chemistry, UC IrvineIrvineUnited States
- Center for Epigenetics and Metabolism, UC IrvineIrvineUnited States
| | - Ron Pulido
- Department of Biological Chemistry, UC IrvineIrvineUnited States
- Center for Epigenetics and Metabolism, UC IrvineIrvineUnited States
| | - Carlos HV Nascimento-Filho
- Department of Biological Chemistry, UC IrvineIrvineUnited States
- Center for Epigenetics and Metabolism, UC IrvineIrvineUnited States
| | - Cholsoon Jang
- Department of Biological Chemistry, UC IrvineIrvineUnited States
- Center for Epigenetics and Metabolism, UC IrvineIrvineUnited States
| | - Ivan Marazzi
- Department of Biological Chemistry, UC IrvineIrvineUnited States
- Center for Epigenetics and Metabolism, UC IrvineIrvineUnited States
| | - Jamie Justice
- Veterans Administration Greater Los Angeles Healthcare System, Geriatric Research Education and Clinical Center (GRECC)Los AngelesUnited States
| | - Nicholas Pannunzio
- Divison of Hematology/Oncology, Department of Medicine, UC Irvine HealthIrvineUnited States
| | - Andrea L Hevener
- Department of Medicine, Division of Endocrinology, Diabetes, and Hypertension, David Geffen School of Medicine at UCLALos AngelesUnited States
- Iris Cantor-UCLA Women’s Health Research Center, David Geffen School of Medicine at UCLALos AngelesUnited States
| | - Lauren Sparks
- Translational Research Institute, AdventHealthOrlandoUnited States
| | - Erin E Kershaw
- Division of Endocrinology, Department of Medicine, University of PittsburgPittsburghUnited States
| | - Dequina Nicholas
- Department of Biological Chemistry, UC IrvineIrvineUnited States
- Center for Epigenetics and Metabolism, UC IrvineIrvineUnited States
- Department of Molecular Biology and Biochemistry, School of Biological Sciences, University of California IrvineIrvineUnited States
| | - Benjamin L Parker
- Department of Anatomy and Physiology, University of MelbourneMelbourneAustralia
| | - Selma Masri
- Department of Biological Chemistry, UC IrvineIrvineUnited States
- Center for Epigenetics and Metabolism, UC IrvineIrvineUnited States
| | - Marcus M Seldin
- Department of Biological Chemistry, UC IrvineIrvineUnited States
- Center for Epigenetics and Metabolism, UC IrvineIrvineUnited States
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5
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Hodonsky CJ, Turner AW, Khan MD, Barrientos NB, Methorst R, Ma L, Lopez NG, Mosquera JV, Auguste G, Farber E, Ma WF, Wong D, Onengut-Gumuscu S, Kavousi M, Peyser PA, van der Laan SW, Leeper NJ, Kovacic JC, Björkegren JLM, Miller CL. Multi-ancestry genetic analysis of gene regulation in coronary arteries prioritizes disease risk loci. Cell Genom 2024; 4:100465. [PMID: 38190101 PMCID: PMC10794848 DOI: 10.1016/j.xgen.2023.100465] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Revised: 09/07/2023] [Accepted: 11/19/2023] [Indexed: 01/09/2024]
Abstract
Genome-wide association studies (GWASs) have identified hundreds of risk loci for coronary artery disease (CAD). However, non-European populations are underrepresented in GWASs, and the causal gene-regulatory mechanisms of these risk loci during atherosclerosis remain unclear. We incorporated local ancestry and haplotypes to identify quantitative trait loci for expression (eQTLs) and splicing (sQTLs) in coronary arteries from 138 ancestrally diverse Americans. Of 2,132 eQTL-associated genes (eGenes), 47% were previously unreported in coronary artery; 19% exhibited cell-type-specific expression. Colocalization revealed subgroups of eGenes unique to CAD and blood pressure GWAS. Fine-mapping highlighted additional eGenes, including TBX20 and IL5. We also identified sQTLs for 1,690 genes, among which TOR1AIP1 and ULK3 sQTLs demonstrated the importance of evaluating splicing to accurately identify disease-relevant isoform expression. Our work provides a patient-derived coronary artery eQTL resource and exemplifies the need for diverse study populations and multifaceted approaches to characterize gene regulation in disease processes.
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Affiliation(s)
- Chani J Hodonsky
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA
| | - Adam W Turner
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA
| | - Mohammad Daud Khan
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA
| | - Nelson B Barrientos
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA; Department of Genetic Medicine, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Ruben Methorst
- Central Diagnostics Laboratory, Division Laboratories, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, Utrecht University, 3584 CX Utrecht, the Netherlands
| | - Lijiang Ma
- Department of Genetics and Genomic Sciences, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Nicolas G Lopez
- Division of Vascular Surgery, Department of Surgery, Stanford University, Stanford, CA 94305, USA
| | - Jose Verdezoto Mosquera
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA; Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA 22908, USA
| | - Gaëlle Auguste
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA
| | - Emily Farber
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA
| | - Wei Feng Ma
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA; Medical Scientist Training Program, Department of Pathology, University of Virginia, Charlottesville, VA 22908, USA
| | - Doris Wong
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA; Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA 22908, USA
| | - Suna Onengut-Gumuscu
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA
| | - Maryam Kavousi
- Department of Epidemiology, Erasmus University Medical Center, 3000 CA Rotterdam, the Netherlands
| | - Patricia A Peyser
- Department of Epidemiology, University of Michigan, Ann Arbor, MI 48019, USA
| | - Sander W van der Laan
- Central Diagnostics Laboratory, Division Laboratories, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, Utrecht University, 3584 CX Utrecht, the Netherlands
| | - Nicholas J Leeper
- Division of Vascular Surgery, Department of Surgery, Stanford University, Stanford, CA 94305, USA
| | - Jason C Kovacic
- Cardiovascular Research Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Victor Chang Cardiac Research Institute, Darlinghurst, NSW 2010, Australia; St. Vincent's Clinical School, University of New South Wales, Sydney, NSW 2052, Australia
| | - Johan L M Björkegren
- Department of Genetics and Genomic Sciences, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Medicine, Huddinge, Karolinska Institutet, 141 52 Huddinge, Sweden
| | - Clint L Miller
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA; Division of Vascular Surgery, Department of Surgery, Stanford University, Stanford, CA 94305, USA; Department of Public Health Sciences, University of Virginia, Charlottesville, VA 22908, USA.
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6
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Martinez-Campanario MC, Cortés M, Moreno-Lanceta A, Han L, Ninfali C, Domínguez V, Andrés-Manzano MJ, Farràs M, Esteve-Codina A, Enrich C, Díaz-Crespo FJ, Pintado B, Escolà-Gil JC, García de Frutos P, Andrés V, Melgar-Lesmes P, Postigo A. Atherosclerotic plaque development in mice is enhanced by myeloid ZEB1 downregulation. Nat Commun 2023; 14:8316. [PMID: 38097578 PMCID: PMC10721632 DOI: 10.1038/s41467-023-43896-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Accepted: 11/23/2023] [Indexed: 12/17/2023] Open
Abstract
Accumulation of lipid-laden macrophages within the arterial neointima is a critical step in atherosclerotic plaque formation. Here, we show that reduced levels of the cellular plasticity factor ZEB1 in macrophages increase atherosclerotic plaque formation and the chance of cardiovascular events. Compared to control counterparts (Zeb1WT/ApoeKO), male mice with Zeb1 ablation in their myeloid cells (Zeb1∆M/ApoeKO) have larger atherosclerotic plaques and higher lipid accumulation in their macrophages due to delayed lipid traffic and deficient cholesterol efflux. Zeb1∆M/ApoeKO mice display more pronounced systemic metabolic alterations than Zeb1WT/ApoeKO mice, with higher serum levels of low-density lipoproteins and inflammatory cytokines and larger ectopic fat deposits. Higher lipid accumulation in Zeb1∆M macrophages is reverted by the exogenous expression of Zeb1 through macrophage-targeted nanoparticles. In vivo administration of these nanoparticles reduces atherosclerotic plaque formation in Zeb1∆M/ApoeKO mice. Finally, low ZEB1 expression in human endarterectomies is associated with plaque rupture and cardiovascular events. These results set ZEB1 in macrophages as a potential target in the treatment of atherosclerosis.
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Affiliation(s)
- M C Martinez-Campanario
- Group of Gene Regulation in Stem Cells, Cell Plasticity, Differentiation, and Cancer, IDIBAPS, 08036, Barcelona, Spain
| | - Marlies Cortés
- Group of Gene Regulation in Stem Cells, Cell Plasticity, Differentiation, and Cancer, IDIBAPS, 08036, Barcelona, Spain
| | - Alazne Moreno-Lanceta
- Department of Biomedicine, University of Barcelona School of Medicine, 08036, Barcelona, Spain
| | - Lu Han
- Group of Gene Regulation in Stem Cells, Cell Plasticity, Differentiation, and Cancer, IDIBAPS, 08036, Barcelona, Spain
| | - Chiara Ninfali
- Group of Gene Regulation in Stem Cells, Cell Plasticity, Differentiation, and Cancer, IDIBAPS, 08036, Barcelona, Spain
| | - Verónica Domínguez
- Transgenesis Facility, National Center of Biotechnology (CNB) and Center for Molecular Biology Severo Ochoa (UAM-CBMSO), Spanish National Research Council (CSIC) and Autonomous University of Madrid (UAM), Cantoblanco, 28049, Madrid, Spain
| | - María J Andrés-Manzano
- Group of Molecular and Genetic Cardiovascular Pathophysiology, Spanish National Center for Cardiovascular Research (CNIC), 28029, Madrid, Spain
- Center for Biomedical, Research Network in Cardiovascular Diseases (CIBERCV), Carlos III Health Institute, 28029, Madrid, Spain
| | - Marta Farràs
- Department of Biochemistry and Molecular Biology, Institute of Biomedical Research Sant Pau, University Autonomous of Barcelona, 08041, Barcelona, Spain
- Center for Biomedical Research Network in Diabetes and Associated Metabolic Diseases (CIBERDEM), Carlos III Health Institute, 28029, Madrid, Spain
| | | | - Carlos Enrich
- Department of Biomedicine, University of Barcelona School of Medicine, 08036, Barcelona, Spain
- Group of signal transduction, intracellular compartments and cancer, IDIBAPS, 08036, Barcelona, Spain
| | - Francisco J Díaz-Crespo
- Department of Pathology, Hospital General Universitario Gregorio Marañón, 28007, Madrid, Spain
| | - Belén Pintado
- Transgenesis Facility, National Center of Biotechnology (CNB) and Center for Molecular Biology Severo Ochoa (UAM-CBMSO), Spanish National Research Council (CSIC) and Autonomous University of Madrid (UAM), Cantoblanco, 28049, Madrid, Spain
| | - Joan C Escolà-Gil
- Department of Biochemistry and Molecular Biology, Institute of Biomedical Research Sant Pau, University Autonomous of Barcelona, 08041, Barcelona, Spain
- Center for Biomedical Research Network in Diabetes and Associated Metabolic Diseases (CIBERDEM), Carlos III Health Institute, 28029, Madrid, Spain
| | - Pablo García de Frutos
- Center for Biomedical, Research Network in Cardiovascular Diseases (CIBERCV), Carlos III Health Institute, 28029, Madrid, Spain
- Department Of Cell Death and Proliferation, Institute for Biomedical Research of Barcelona (IIBB), Spanish National Research Council (CSIC), 08036, Barcelona, Spain
- Group of Hemotherapy and Hemostasis, IDIBAPS, 08036, Barcelona, Spain
| | - Vicente Andrés
- Group of Molecular and Genetic Cardiovascular Pathophysiology, Spanish National Center for Cardiovascular Research (CNIC), 28029, Madrid, Spain
- Center for Biomedical, Research Network in Cardiovascular Diseases (CIBERCV), Carlos III Health Institute, 28029, Madrid, Spain
| | - Pedro Melgar-Lesmes
- Department of Biomedicine, University of Barcelona School of Medicine, 08036, Barcelona, Spain
- Department of Biochemistry and Molecular Genetics, Hospital Clínic, 08036, Barcelona, Spain
- Center for Biomedical Research Network in Gastrointestinal and Liver Diseases (CIBEREHD), Carlos III Health Institute, 28029, Madrid, Spain
- Institute for Medical Engineering & Science, Massachusetts Institute of Technology (MIT), Cambridge, MA, 02139, USA
| | - Antonio Postigo
- Group of Gene Regulation in Stem Cells, Cell Plasticity, Differentiation, and Cancer, IDIBAPS, 08036, Barcelona, Spain.
- Center for Biomedical Research Network in Gastrointestinal and Liver Diseases (CIBEREHD), Carlos III Health Institute, 28029, Madrid, Spain.
- Molecular Targets Program, Division of Oncology, Department of Medicine, J.G. Brown Cancer Center, Louisville, KY, 40202, USA.
- ICREA, 08010, Barcelona, Spain.
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Cheng J, Cheng M, Lusis AJ, Yang X. Gene Regulatory Networks in Coronary Artery Disease. Curr Atheroscler Rep 2023; 25:1013-1023. [PMID: 38008808 DOI: 10.1007/s11883-023-01170-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/09/2023] [Indexed: 11/28/2023]
Abstract
PURPOSE OF REVIEW Coronary artery disease is a complex disorder and the leading cause of mortality worldwide. As technologies for the generation of high-throughput multiomics data have advanced, gene regulatory network modeling has become an increasingly powerful tool in understanding coronary artery disease. This review summarizes recent and novel gene regulatory network tools for bulk tissue and single cell data, existing databases for network construction, and applications of gene regulatory networks in coronary artery disease. RECENT FINDINGS New gene regulatory network tools can integrate multiomics data to elucidate complex disease mechanisms at unprecedented cellular and spatial resolutions. At the same time, updates to coronary artery disease expression data in existing databases have enabled researchers to build gene regulatory networks to study novel disease mechanisms. Gene regulatory networks have proven extremely useful in understanding CAD heritability beyond what is explained by GWAS loci and in identifying mechanisms and key driver genes underlying disease onset and progression. Gene regulatory networks can holistically and comprehensively address the complex nature of coronary artery disease. In this review, we discuss key algorithmic approaches to construct gene regulatory networks and highlight state-of-the-art methods that model specific modes of gene regulation. We also explore recent applications of these tools in coronary artery disease patient data repositories to understand disease heritability and shared and distinct disease mechanisms and key driver genes across tissues, between sexes, and between species.
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Grants
- DK120342, HL148577, and HL147883 (AJL). NS111378, NS117148, HL147883 (XY) NIH HHS
- DK120342, HL148577, and HL147883 (AJL). NS111378, NS117148, HL147883 (XY) NIH HHS
- DK120342, HL148577, and HL147883 (AJL). NS111378, NS117148, HL147883 (XY) NIH HHS
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Affiliation(s)
- Jenny Cheng
- Department of Integrative Biology and Physiology, University of California, Los Angeles, 610 Charles E. Young Drive East, Los Angeles, CA, 90095, USA
- Molecular, Cellular and Integrative Physiology Interdepartmental Program, University of California, Los Angeles, 610 Charles E. Young Drive East, Los Angeles, CA, 90095, USA
| | - Michael Cheng
- Department of Integrative Biology and Physiology, University of California, Los Angeles, 610 Charles E. Young Drive East, Los Angeles, CA, 90095, USA
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, 610 Charles E. Young Drive East, Los Angeles, CA, 90095, USA
| | - Aldons J Lusis
- Department of Medicine, Division of Cardiology, University of California, Los Angeles, 650 Charles E Young Drive South, Los Angeles, CA, 90095, USA.
- Departments of Human Genetics & Microbiology, Immunology, and Molecular Genetics, University of California, Los Angeles, 650 Charles E. Young Drive South, Los Angeles, CA, 90095, USA.
| | - Xia Yang
- Department of Integrative Biology and Physiology, University of California, Los Angeles, 610 Charles E. Young Drive East, Los Angeles, CA, 90095, USA.
- Molecular, Cellular and Integrative Physiology Interdepartmental Program, University of California, Los Angeles, 610 Charles E. Young Drive East, Los Angeles, CA, 90095, USA.
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, 610 Charles E. Young Drive East, Los Angeles, CA, 90095, USA.
- Department of Molecular and Medical Pharmacology, University of California, Los Angeles, 610 Charles E. Young Drive East, Los Angeles, CA, 90095, USA.
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8
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Scarpa J. Improving liver transplant outcomes with transplant-omics and network biology. Curr Opin Organ Transplant 2023; 28:412-418. [PMID: 37706301 DOI: 10.1097/mot.0000000000001100] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/15/2023]
Abstract
PURPOSE OF REVIEW Molecular omics data is increasingly ubiquitous throughout medicine. In organ transplantation, recent large-scale research efforts are generating the 'transplant-ome' - the entire set of molecular omics data, including the genome, transcriptome, proteome, and metabolome. Importantly, early studies in anesthesiology have demonstrated how perioperative interventions alter molecular profiles in various patient populations. The next step for anesthesiologists and intensivists will be to tailor perioperative care to the transplant-ome of individual liver transplant patients. RECENT FINDINGS In liver transplant patients, elements of the transplant-ome predict complications and point to novel interventions. Importantly, molecular profiles of both the donor organ and recipient contribute to this risk, and interventions like normothermic machine perfusion influence these profiles. As we can now measure various omics molecules simultaneously, we can begin to understand how these molecules interact to form molecular networks and emerging technologies offer noninvasive and continuous ways to measure these networks throughout the perioperative period. Molecules that regulate these networks are likely mediators of complications and actionable clinical targets throughout the perioperative period. SUMMARY The transplant-ome can be used to tailor perioperative care to the individual liver transplant patient. Monitoring molecular networks continuously and noninvasively would provide new opportunities to optimize perioperative management.
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Affiliation(s)
- Joseph Scarpa
- Department of Anesthesiology, Weill Cornell Medicine, New York, New York, USA
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9
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Liu J, Hu S, Chen L, Daly C, Prada Medina CA, Richardson TG, Traylor M, Dempster NJ, Mbasu R, Monfeuga T, Vujkovic M, Tsao PS, Lynch JA, Voight BF, Chang KM, Million VA, Cobbold JF, Tomlinson JW, van Duijn CM, Howson JMM. Profiling the genome and proteome of metabolic dysfunction-associated steatotic liver disease identifies potential therapeutic targets. medRxiv 2023:2023.11.30.23299247. [PMID: 38076879 PMCID: PMC10705663 DOI: 10.1101/2023.11.30.23299247] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/21/2023]
Abstract
BACKGROUND & AIMS Metabolic dysfunction-associated steatotic liver disease (MASLD) affects over 25% of the population and currently has no effective treatments. Plasma proteins with causal evidence may represent promising drug targets. We aimed to identify plasma proteins in the causal pathway of MASLD and explore their interaction with obesity. METHODS We analysed 2,941 plasma proteins in 43,978 European participants from UK Biobank. We performed genome-wide association study (GWAS) for all MASLD-associated proteins and created the largest MASLD GWAS (109,885 cases/1,014,923 controls). We performed Mendelian Randomization (MR) and integrated proteins and their encoding genes in MASLD ranges to identify candidate causal proteins. We then validated them through independent replication, exome sequencing, liver imaging, bulk and single-cell gene expression, liver biopsies, pathway, and phenome-wide data. We explored the role of obesity by MR and multivariable MR across proteins, body mass index, and MASLD. RESULTS We found 929 proteins associated with MASLD, reported five novel genetic loci associated with MASLD, and identified 17 candidate MASLD protein targets. We identified four novel targets for MASLD (CD33, GRHPR, HMOX2, and SCG3), provided protein evidence supporting roles of AHCY, FCGR2B, ORM1, and RBKS in MASLD, and validated nine previously known targets. We found that CD33, FCGR2B, ORM1, RBKS, and SCG3 mediated the association of obesity and MASLD, and HMOX2, ORM1, and RBKS had effect on MASLD independent of obesity. CONCLUSIONS This study identified new protein targets in the causal pathway of MASLD, providing new insights into the multi-omics architecture and pathophysiology of MASLD. These findings advise further therapeutic interventions for MASLD.
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Affiliation(s)
- Jun Liu
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Genetics Centre-of-Excellence, Novo Nordisk Research Centre Oxford, Oxford, UK
| | - Sile Hu
- Genetics Centre-of-Excellence, Novo Nordisk Research Centre Oxford, Oxford, UK
| | - Lingyan Chen
- Genetics Centre-of-Excellence, Novo Nordisk Research Centre Oxford, Oxford, UK
| | - Charlotte Daly
- Department of Discovery Technology and Genomics, Novo Nordisk Research Centre Oxford, Oxford, UK
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Oxford, UK
| | | | - Tom G Richardson
- Genetics Centre-of-Excellence, Novo Nordisk Research Centre Oxford, Oxford, UK
- MRC Integrative Epidemiology Unit (IEU), Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Matthew Traylor
- Genetics Centre-of-Excellence, Novo Nordisk Research Centre Oxford, Oxford, UK
| | - Niall J Dempster
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Oxford, UK
| | - Richard Mbasu
- Department of Discovery Technology and Genomics, Novo Nordisk Research Centre Oxford, Oxford, UK
| | - Thomas Monfeuga
- AI & Digital Research, Research & Early Development, Novo Nordisk Research Centre Oxford, UK
| | - Marijana Vujkovic
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Philip S Tsao
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- Department of Cardiovascular Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - Julie A Lynch
- VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, Utah, USA
- Department of Internal Medicine, School of Medicine, University of Utah, Salt Lake City, Utah, USA
| | - Benjamin F Voight
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Kyong-Mi Chang
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - V A Million
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Genetics Centre-of-Excellence, Novo Nordisk Research Centre Oxford, Oxford, UK
- Department of Discovery Technology and Genomics, Novo Nordisk Research Centre Oxford, Oxford, UK
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Oxford, UK
- AI & Digital Research, Research & Early Development, Novo Nordisk Research Centre Oxford, UK
- MRC Integrative Epidemiology Unit (IEU), Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- Department of Cardiovascular Medicine, School of Medicine, Stanford University, Stanford, CA, USA
- VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, Utah, USA
- Department of Internal Medicine, School of Medicine, University of Utah, Salt Lake City, Utah, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust and the University of Oxford, Oxford, UK
- Translational Gastroenterology Unit, University of Oxford, Oxford, UK
| | - Jeremy F Cobbold
- NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust and the University of Oxford, Oxford, UK
- Translational Gastroenterology Unit, University of Oxford, Oxford, UK
| | - Jeremy W Tomlinson
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Oxford, UK
- NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust and the University of Oxford, Oxford, UK
| | | | - Joanna M M Howson
- Genetics Centre-of-Excellence, Novo Nordisk Research Centre Oxford, Oxford, UK
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10
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Savić R, Yang J, Koplev S, An MC, Patel PL, O'Brien RN, Dubose BN, Dodatko T, Rogatsky E, Sukhavasi K, Ermel R, Ruusalepp A, Houten SM, Kovacic JC, Stewart AF, Yohn CB, Schadt EE, Laberge RM, Björkegren JLM, Tu Z, Argmann C. Integration of transcriptomes of senescent cell models with multi-tissue patient samples reveals reduced COL6A3 as an inducer of senescence. Cell Rep 2023; 42:113371. [PMID: 37938972 PMCID: PMC10955802 DOI: 10.1016/j.celrep.2023.113371] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Revised: 05/23/2023] [Accepted: 10/17/2023] [Indexed: 11/10/2023] Open
Abstract
Senescent cells are a major contributor to age-dependent cardiovascular tissue dysfunction, but knowledge of their in vivo cell markers and tissue context is lacking. To reveal tissue-relevant senescence biology, we integrate the transcriptomes of 10 experimental senescence cell models with a 224 multi-tissue gene co-expression network based on RNA-seq data of seven tissues biopsies from ∼600 coronary artery disease (CAD) patients. We identify 56 senescence-associated modules, many enriched in CAD GWAS genes and correlated with cardiometabolic traits-which supports universality of senescence gene programs across tissues and in CAD. Cross-tissue network analyses reveal 86 candidate senescence-associated secretory phenotype (SASP) factors, including COL6A3. Experimental knockdown of COL6A3 induces transcriptional changes that overlap the majority of the experimental senescence models, with cell-cycle arrest linked to modulation of DREAM complex-targeted genes. We provide a transcriptomic resource for cellular senescence and identify candidate biomarkers, SASP factors, and potential drivers of senescence in human tissues.
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Affiliation(s)
- Radoslav Savić
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029-6574, USA
| | - Jialiang Yang
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029-6574, USA
| | - Simon Koplev
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge, UK
| | - Mahru C An
- UNITY Biotechnology, South San Francisco, CA 94080, USA
| | | | | | | | - Tetyana Dodatko
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029-6574, USA
| | - Eduard Rogatsky
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029-6574, USA
| | - Katyayani Sukhavasi
- Department of Cardiac Surgery and The Heart Clinic, Tartu University Hospital, Tartu, Estonia
| | - Raili Ermel
- Department of Cardiac Surgery and The Heart Clinic, Tartu University Hospital, Tartu, Estonia
| | - Arno Ruusalepp
- Department of Cardiac Surgery and The Heart Clinic, Tartu University Hospital, Tartu, Estonia; Clinical Gene Networks AB, Stockholm, Sweden
| | - Sander M Houten
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029-6574, USA
| | - Jason C Kovacic
- Cardiovascular Research Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029-6574, USA; Victor Chang Cardiac Research Institute, Darlinghurst, NSW, Australia; St. Vincent's Clinical School, University of New South Wales, Sydney, NSW, Australia
| | - Andrew F Stewart
- Diabetes Obesity Metabolism Institute, The Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | | | - Eric E Schadt
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029-6574, USA
| | | | - Johan L M Björkegren
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029-6574, USA; Clinical Gene Networks AB, Stockholm, Sweden; Department of Medicine, Karolinska Institutet, Karolinska Universitetssjukhuset, Huddinge, Sweden
| | - Zhidong Tu
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029-6574, USA
| | - Carmen Argmann
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029-6574, USA.
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11
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Mosquera JV, Auguste G, Wong D, Turner AW, Hodonsky CJ, Alvarez-Yela AC, Song Y, Cheng Q, Lino Cardenas CL, Theofilatos K, Bos M, Kavousi M, Peyser PA, Mayr M, Kovacic JC, Björkegren JLM, Malhotra R, Stukenberg PT, Finn AV, van der Laan SW, Zang C, Sheffield NC, Miller CL. Integrative single-cell meta-analysis reveals disease-relevant vascular cell states and markers in human atherosclerosis. Cell Rep 2023; 42:113380. [PMID: 37950869 DOI: 10.1016/j.celrep.2023.113380] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2023] [Revised: 09/12/2023] [Accepted: 10/20/2023] [Indexed: 11/13/2023] Open
Abstract
Coronary artery disease (CAD) is characterized by atherosclerotic plaque formation in the arterial wall. CAD progression involves complex interactions and phenotypic plasticity among vascular and immune cell lineages. Single-cell RNA-seq (scRNA-seq) studies have highlighted lineage-specific transcriptomic signatures, but human cell phenotypes remain controversial. Here, we perform an integrated meta-analysis of 22 scRNA-seq libraries to generate a comprehensive map of human atherosclerosis with 118,578 cells. Besides characterizing granular cell-type diversity and communication, we leverage this atlas to provide insights into smooth muscle cell (SMC) modulation. We integrate genome-wide association study data and uncover a critical role for modulated SMC phenotypes in CAD, myocardial infarction, and coronary calcification. Finally, we identify fibromyocyte/fibrochondrogenic SMC markers (LTBP1 and CRTAC1) as proxies of atherosclerosis progression and validate these through omics and spatial imaging analyses. Altogether, we create a unified atlas of human atherosclerosis informing cell state-specific mechanistic and translational studies of cardiovascular diseases.
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Affiliation(s)
- Jose Verdezoto Mosquera
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA 22908, USA; Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA
| | - Gaëlle Auguste
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA
| | - Doris Wong
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA 22908, USA; Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA
| | - Adam W Turner
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA
| | - Chani J Hodonsky
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA
| | | | - Yipei Song
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA; Department of Computer Engineering, University of Virginia, Charlottesville, VA 22908, USA
| | - Qi Cheng
- CVPath Institute, Gaithersburg, MD 20878, USA
| | - Christian L Lino Cardenas
- Cardiovascular Research Center, Cardiology Division, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02129, USA
| | | | - Maxime Bos
- Department of Epidemiology, Erasmus University Medical Center, 3000 CA Rotterdam, the Netherlands
| | - Maryam Kavousi
- Department of Epidemiology, Erasmus University Medical Center, 3000 CA Rotterdam, the Netherlands
| | - Patricia A Peyser
- Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI 48019, USA
| | - Manuel Mayr
- King's British Heart Foundation Centre, King's College London, London WC2R 2LS, UK; National Heart and Lung Institute, Imperial College London, London SW3 6LY, UK
| | - Jason C Kovacic
- Cardiovascular Research Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Victor Chang Cardiac Research Institute, Darlinghurst, NSW 2010, Australia; St. Vincent's Clinical School, University of New South Wales, Sydney, NSW 2052, Australia
| | - Johan L M Björkegren
- Department of Genetics and Genomic Sciences, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Medicine, Karolinska Institutet, 141 52 Huddinge, Sweden
| | - Rajeev Malhotra
- Cardiovascular Research Center, Cardiology Division, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02129, USA
| | - P Todd Stukenberg
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA 22908, USA
| | | | - Sander W van der Laan
- Central Diagnostics Laboratory, Division Laboratories, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, Utrecht University, 3584 CX Utrecht, the Netherlands
| | - Chongzhi Zang
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA 22908, USA; Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA; Department of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908, USA; Department of Public Health Sciences, University of Virginia, Charlottesville, VA 22908, USA
| | - Nathan C Sheffield
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA 22908, USA; Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA; Department of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908, USA; Department of Public Health Sciences, University of Virginia, Charlottesville, VA 22908, USA
| | - Clint L Miller
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA 22908, USA; Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA; Department of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908, USA; Department of Public Health Sciences, University of Virginia, Charlottesville, VA 22908, USA.
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Allayee H, Farber CR, Seldin MM, Williams EG, James DE, Lusis AJ. Systems genetics approaches for understanding complex traits with relevance for human disease. eLife 2023; 12:e91004. [PMID: 37962168 PMCID: PMC10645424 DOI: 10.7554/elife.91004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Accepted: 10/16/2023] [Indexed: 11/15/2023] Open
Abstract
Quantitative traits are often complex because of the contribution of many loci, with further complexity added by environmental factors. In medical research, systems genetics is a powerful approach for the study of complex traits, as it integrates intermediate phenotypes, such as RNA, protein, and metabolite levels, to understand molecular and physiological phenotypes linking discrete DNA sequence variation to complex clinical and physiological traits. The primary purpose of this review is to describe some of the resources and tools of systems genetics in humans and rodent models, so that researchers in many areas of biology and medicine can make use of the data.
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Affiliation(s)
- Hooman Allayee
- Departments of Population & Public Health Sciences, University of Southern CaliforniaLos AngelesUnited States
- Biochemistry & Molecular Medicine, Keck School of Medicine, University of Southern CaliforniaLos AngelesUnited States
| | - Charles R Farber
- Center for Public Health Genomics, University of Virginia School of MedicineCharlottesvilleUnited States
- Departments of Biochemistry & Molecular Genetics, University of Virginia School of MedicineCharlottesvilleUnited States
- Public Health Sciences, University of Virginia School of MedicineCharlottesvilleUnited States
| | - Marcus M Seldin
- Department of Biological Chemistry, University of California, IrvineIrvineUnited States
| | - Evan Graehl Williams
- Luxembourg Centre for Systems Biomedicine, University of LuxembourgLuxembourgLuxembourg
| | - David E James
- School of Life and Environmental Sciences, University of SydneyCamperdownAustralia
- Faculty of Medicine and Health, University of SydneyCamperdownAustralia
- Charles Perkins Centre, University of SydneyCamperdownAustralia
| | - Aldons J Lusis
- Departments of Human Genetics, University of California, Los AngelesLos AngelesUnited States
- Medicine, University of California, Los AngelesLos AngelesUnited States
- Microbiology, Immunology, & Molecular Genetics, David Geffen School of Medicine of UCLALos AngelesUnited States
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13
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Sakkers TR, Mokry M, Civelek M, Erdmann J, Pasterkamp G, Diez Benavente E, den Ruijter HM. Sex differences in the genetic and molecular mechanisms of coronary artery disease. Atherosclerosis 2023; 384:117279. [PMID: 37805337 DOI: 10.1016/j.atherosclerosis.2023.117279] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/11/2023] [Revised: 05/09/2023] [Accepted: 09/01/2023] [Indexed: 10/09/2023]
Abstract
Sex differences in coronary artery disease (CAD) presentation, risk factors and prognosis have been widely studied. Similarly, studies on atherosclerosis have shown prominent sex differences in plaque biology. Our understanding of the underlying genetic and molecular mechanisms that drive these differences remains fragmented and largely understudied. Through reviewing genetic and epigenetic studies, we identified more than 40 sex-differential candidate genes (13 within known CAD loci) that may explain, at least in part, sex differences in vascular remodeling, lipid metabolism and endothelial dysfunction. Studies with transcriptomic and single-cell RNA sequencing data from atherosclerotic plaques highlight potential sex differences in smooth muscle cell and endothelial cell biology. Especially, phenotypic switching of smooth muscle cells seems to play a crucial role in female atherosclerosis. This matches the known sex differences in atherosclerotic phenotypes, with men being more prone to lipid-rich plaques, while women are more likely to develop fibrous plaques with endothelial dysfunction. To unravel the complex mechanisms that drive sex differences in CAD, increased statistical power and adjustments to study designs and analysis strategies are required. This entails increasing inclusion rates of women, performing well-defined sex-stratified analyses and the integration of multi-omics data.
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Affiliation(s)
- Tim R Sakkers
- Laboratory of Experimental Cardiology, University Medical Center Utrecht, Utrecht University, Heidelberglaan 100, 3508, GA, Utrecht, the Netherlands
| | - Michal Mokry
- Laboratory of Experimental Cardiology, University Medical Center Utrecht, Utrecht University, Heidelberglaan 100, 3508, GA, Utrecht, the Netherlands; Central Diagnostic Laboratory, University Medical Center Utrecht, Utrecht University, Heidelberglaan 100, 3508, GA, Utrecht, the Netherlands
| | - Mete Civelek
- Center for Public Health Genomics, University of Virginia, 1335 Lee St, Charlottesville, VA, 22908, USA; Department of Biomedical Engineering, University of Virginia, 351 McCormick Road, Charlottesville, VA, 22904, USA
| | - Jeanette Erdmann
- Institute for Cardiogenetics, University of Lübeck, Ratzeburger Allee 160, 23562, Lübeck, Germany
| | - Gerard Pasterkamp
- Central Diagnostic Laboratory, University Medical Center Utrecht, Utrecht University, Heidelberglaan 100, 3508, GA, Utrecht, the Netherlands
| | - Ernest Diez Benavente
- Laboratory of Experimental Cardiology, University Medical Center Utrecht, Utrecht University, Heidelberglaan 100, 3508, GA, Utrecht, the Netherlands
| | - Hester M den Ruijter
- Laboratory of Experimental Cardiology, University Medical Center Utrecht, Utrecht University, Heidelberglaan 100, 3508, GA, Utrecht, the Netherlands.
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Duan W, Shi R, Yang F, Zhou Z, Wang L, Huang Z, Zang S. FSTL3 partially mediates the association of increased nonalcoholic fatty liver disease fibrosis risk with acute myocardial infarction in patients with type 2 diabetes mellitus. Cardiovasc Diabetol 2023; 22:297. [PMID: 37904173 PMCID: PMC10617048 DOI: 10.1186/s12933-023-02024-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Accepted: 10/11/2023] [Indexed: 11/01/2023] Open
Abstract
BACKGROUND The study aimed to investigate an association of increased liver fibrosis with acute myocardial infarction (AMI), and to investigate the mediating effect of serum follistatin-like protein 3 (FSTL3) on the association in patients with type 2 diabetes mellitus (T2DM). METHOD A total of 1424 participants were included in this study, and were firstly divided into two groups: 429 T2DM patients and 995 T2DM patients with NAFLD to assess the association of NAFLD and AMI. Then 995 T2DM co-existent NAFLD patients were categorized by NAFLD fibrosis risk to explore the association between NAFLD fibrosis risk and AMI. Immunohistochemistry staining and semi-quantitative analysis of liver FSTL3 were performed in 60 patients with NAFLD. There were 323 individuals (191 without AMI and 132 with AMI) in T2DM co-existent NAFLD patients who had serum samples, and serum FSTL3 was tested and mediation effect of FSTL3 in association of NAFLD fibrosis and AMI was performed. RESULTS First, increased NAFLD fibrosis risk was an independent risk factor for AMI in patients with T2DM and co-existent NAFLD. In addition, analysis of Gene Expression Omnibus (GEO) database and immunohistochemical staining confirmed the increased expression of FSTL3 in the liver of NAFLD patients with fibrosis. Serum FSTL3 significantly increased in patients with high NAFLD fibrosis risk and AMI, and closely associated with NAFLD fibrosis and AMI severity in T2DM patients with co-existent NAFLD. Most importantly, analysis of the level of mediation revealed that increased serum FSTL3 partially mediated the association of increased NAFLD fibrosis risk with AMI in T2DM patients with co-existent NAFLD. CONCLUSIONS NAFLD fibrosis was closely associated with AMI in T2DM patients. FSTL3 expression was enriched in the liver of NAFLD patients with significant and advanced fibrosis, and serum FSTL3 partially mediated the association of increased liver fibrosis risk with AMI in T2DM patients.
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Affiliation(s)
- Wenfei Duan
- Department of Endocrinology, The Fifth People's Hospital of Shanghai, Fudan University, 801 Heqing Road, Minhang District, Shanghai, 200240, China
| | - Ruixiao Shi
- Department of Traditional Chinese Medicine, Maqiao Community Health Service Center, Minhang District, Shanghai, 20111, China
- Center of Community-Based Health Research, Fudan University, Shanghai, China
| | - Fang Yang
- Department of Genetics and Developmental Science, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, China
| | - Zhoujunhao Zhou
- Department of Endocrinology, The Fifth People's Hospital of Shanghai, Fudan University, 801 Heqing Road, Minhang District, Shanghai, 200240, China
| | - Lihong Wang
- Department of Endocrinology, The Fifth People's Hospital of Shanghai, Fudan University, 801 Heqing Road, Minhang District, Shanghai, 200240, China
| | - Zhe Huang
- Department of Genetics and Developmental Science, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, China.
| | - Shufei Zang
- Department of Endocrinology, The Fifth People's Hospital of Shanghai, Fudan University, 801 Heqing Road, Minhang District, Shanghai, 200240, China.
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Benberin V, Karabaeva R, Kulmyrzaeva N, Bigarinova R, Vochshenkova T. Evolution of the search for a common mechanism of congenital risk of coronary heart disease and type 2 diabetes mellitus in the chromosomal locus 9p21.3. Medicine (Baltimore) 2023; 102:e35074. [PMID: 37832109 PMCID: PMC10578751 DOI: 10.1097/md.0000000000035074] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Accepted: 08/14/2023] [Indexed: 10/15/2023] Open
Abstract
9.21.3 chromosomal locus predisposes to coronary heart disease (CHD) and type 2 diabetes mellitus (DM2), but their overall pathological mechanism and clinical applicability remain unclear. The review uses publications of the study results of 9.21.3 chromosomal locus in association with CHD and DM2, which are important for changing the focus of clinical practice. The eligibility criteria are full-text articles published in the PubMed database (MEDLINE) up to December 31, 2022. A total of 56 publications were found that met the inclusion criteria. Using the examples of the progressive stages in understanding the role of the chromosomal locus 9p.21.3, scientific ideas were grouped, from a fragmentary study of independent pathological processes to a systematic study of the overall development of CHD and DM2. The presented review can become a source of new scientific hypotheses for further studies, the results of which can determine the general mechanism of the congenital risk of CHD and DM2 and change the focus of clinical practice.
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Affiliation(s)
- Valeriy Benberin
- Centre of Gerontology, Medical Center Hospital of the President’s Affairs Administration of the Republic of Kazakhstan, Astana, Kazakhstan
| | - Raushan Karabaeva
- Centre of Gerontology, Medical Center Hospital of the President’s Affairs Administration of the Republic of Kazakhstan, Astana, Kazakhstan
| | - Nazgul Kulmyrzaeva
- Centre of Gerontology, Medical Center Hospital of the President’s Affairs Administration of the Republic of Kazakhstan, Astana, Kazakhstan
| | - Rauza Bigarinova
- Centre of Gerontology, Medical Center Hospital of the President’s Affairs Administration of the Republic of Kazakhstan, Astana, Kazakhstan
| | - Tamara Vochshenkova
- Centre of Gerontology, Medical Center Hospital of the President’s Affairs Administration of the Republic of Kazakhstan, Astana, Kazakhstan
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16
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Zhou M, Tamburini IJ, Van C, Molendijk J, Nguyen CM, Chang IYY, Johnson C, Velez LM, Cheon Y, Yeo RX, Bae H, Le J, Larson N, Pulido R, Filho C, Jang C, Marazzi I, Justice JN, Pannunzio N, Hevener A, Sparks LM, Kershaw EE, Nicholas D, Parker B, Masri S, Seldin M. Leveraging inter-individual transcriptional correlation structure to infer discrete signaling mechanisms across metabolic tissues. bioRxiv 2023:2023.05.10.540142. [PMID: 37214953 PMCID: PMC10197628 DOI: 10.1101/2023.05.10.540142] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
Abstract/IntroductionInter-organ communication is a vital process to maintain physiologic homeostasis, and its dysregulation contributes to many human diseases. Beginning with the discovery of insulin over a century ago, characterization of molecules responsible for signal between tissues has required careful and elegant experimentation where these observations have been integral to deciphering physiology and disease. Given that circulating bioactive factors are stable in serum, occur naturally, and are easily assayed from blood, they present obvious focal molecules for therapeutic intervention and biomarker development. For example, physiologic dissection of the actions of soluble proteins such as proprotein convertase subtilisin/kexin type 9 (PCSK9) and glucagon-like peptide 1 (GLP1) have yielded among the most promising therapeutics to treat cardiovascular disease and obesity, respectively1–4. A major obstacle in the characterization of such soluble factors is that defining their tissues and pathways of action requires extensive experimental testing in cells and animal models. Recently, studies have shown that secreted proteins mediating inter-tissue signaling could be identified by “brute-force” surveys of all genes within RNA-sequencing measures across tissues within a population5–9. Expanding on this intuition, we reasoned that parallel strategies could be used to understand how individual genes mediate signaling across metabolic tissues through correlative analyses of gene variation between individuals. Thus, comparison of quantitative levels of gene expression relationships between organs in a population could aid in understanding cross-organ signaling. Here, we surveyed gene-gene correlation structure across 18 metabolic tissues in 310 human individuals and 7 tissues in 103 diverse strains of mice fed a normal chow or HFHS diet. Variation of genes such asFGF21, ADIPOQ, GCGandIL6showed enrichments which recapitulate experimental observations. Further, similar analyses were applied to explore both within-tissue signaling mechanisms (liverPCSK9) as well as genes encoding enzymes producing metabolites (adiposePNPLA2), where inter-individual correlation structure aligned with known roles for these critical metabolic pathways. Examination of sex hormone receptor correlations in mice highlighted the difference of tissue-specific variation in relationships with metabolic traits. We refer to this resource asGene-DerivedCorrelationsAcrossTissues (GD-CAT) where all tools and data are built into a web portal enabling users to perform these analyses without a single line of code (gdcat.org). This resource enables querying of any gene in any tissue to find correlated patterns of genes, cell types, pathways and network architectures across metabolic organs.
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Affiliation(s)
- Mingqi Zhou
- Department of Biological Chemistry, UC Irvine. Irvine, CA, USA
- Center for Epigenetics and Metabolism, UC Irvine. Irvine, CA, USA
| | - Ian J. Tamburini
- Department of Biological Chemistry, UC Irvine. Irvine, CA, USA
- Center for Epigenetics and Metabolism, UC Irvine. Irvine, CA, USA
| | - Cassandra Van
- Department of Biological Chemistry, UC Irvine. Irvine, CA, USA
- Center for Epigenetics and Metabolism, UC Irvine. Irvine, CA, USA
| | - Jeffrey Molendijk
- Department of Anatomy and Physiology, University of Melbourne, Melbourne, VIC, Australia
| | - Christy M Nguyen
- Department of Biological Chemistry, UC Irvine. Irvine, CA, USA
- Center for Epigenetics and Metabolism, UC Irvine. Irvine, CA, USA
| | | | - Casey Johnson
- Department of Biological Chemistry, UC Irvine. Irvine, CA, USA
- Center for Epigenetics and Metabolism, UC Irvine. Irvine, CA, USA
| | - Leandro M. Velez
- Department of Biological Chemistry, UC Irvine. Irvine, CA, USA
- Center for Epigenetics and Metabolism, UC Irvine. Irvine, CA, USA
| | - Youngseo Cheon
- Department of Biological Chemistry, UC Irvine. Irvine, CA, USA
- Center for Epigenetics and Metabolism, UC Irvine. Irvine, CA, USA
| | - Reichelle X. Yeo
- Translational Research Institute, AdventHealth, Orlando, FL, USA
| | - Hosung Bae
- Department of Biological Chemistry, UC Irvine. Irvine, CA, USA
- Center for Epigenetics and Metabolism, UC Irvine. Irvine, CA, USA
| | - Johnny Le
- Department of Biological Chemistry, UC Irvine. Irvine, CA, USA
- Center for Epigenetics and Metabolism, UC Irvine. Irvine, CA, USA
| | - Natalie Larson
- Department of Biological Chemistry, UC Irvine. Irvine, CA, USA
- Center for Epigenetics and Metabolism, UC Irvine. Irvine, CA, USA
| | - Ron Pulido
- Department of Biological Chemistry, UC Irvine. Irvine, CA, USA
- Center for Epigenetics and Metabolism, UC Irvine. Irvine, CA, USA
| | - Carlos Filho
- Department of Biological Chemistry, UC Irvine. Irvine, CA, USA
- Center for Epigenetics and Metabolism, UC Irvine. Irvine, CA, USA
| | - Cholsoon Jang
- Department of Biological Chemistry, UC Irvine. Irvine, CA, USA
- Center for Epigenetics and Metabolism, UC Irvine. Irvine, CA, USA
| | - Ivan Marazzi
- Department of Biological Chemistry, UC Irvine. Irvine, CA, USA
- Center for Epigenetics and Metabolism, UC Irvine. Irvine, CA, USA
| | - Jamie N. Justice
- Veterans Administration Greater Los Angeles Healthcare System, Geriatric Research Education and Clinical Center (GRECC), Los Angeles, CA, USA
| | - Nicholas Pannunzio
- Department of Biological Chemistry, UC Irvine. Irvine, CA, USA
- Center for Epigenetics and Metabolism, UC Irvine. Irvine, CA, USA
| | - Andrea Hevener
- Department of Medicine, Division of Endocrinology, Diabetes, and Hypertension, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
- Iris Cantor-UCLA Women’s Health Research Center, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Lauren M. Sparks
- Translational Research Institute, AdventHealth, Orlando, FL, USA
| | - Erin E. Kershaw
- Department of Internal Medicine, Section On Gerontology and Geriatric Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Dequina Nicholas
- Division of Endocrinology, Department of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Benjamin Parker
- Department of Anatomy and Physiology, University of Melbourne, Melbourne, VIC, Australia
| | - Selma Masri
- Department of Biological Chemistry, UC Irvine. Irvine, CA, USA
- Center for Epigenetics and Metabolism, UC Irvine. Irvine, CA, USA
| | - Marcus Seldin
- Department of Biological Chemistry, UC Irvine. Irvine, CA, USA
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Michoel T, Zhang JD. Causal inference in drug discovery and development. Drug Discov Today 2023; 28:103737. [PMID: 37591410 DOI: 10.1016/j.drudis.2023.103737] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2022] [Revised: 07/31/2023] [Accepted: 08/10/2023] [Indexed: 08/19/2023]
Abstract
To discover new drugs is to seek and to prove causality. As an emerging approach leveraging human knowledge and creativity, data, and machine intelligence, causal inference holds the promise of reducing cognitive bias and improving decision-making in drug discovery. Although it has been applied across the value chain, the concepts and practice of causal inference remain obscure to many practitioners. This article offers a nontechnical introduction to causal inference, reviews its recent applications, and discusses opportunities and challenges of adopting the causal language in drug discovery and development.
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Affiliation(s)
- Tom Michoel
- Computational Biology Unit, Department of Informatics, University of Bergen, Postboks 7803, 5020 Bergen, Norway
| | - Jitao David Zhang
- Pharma Early Research and Development, Roche Innovation Centre Basel, F. Hoffmann-La Roche, Grenzacherstrasse 124, 4070 Basel, Switzerland; Department of Mathematics and Computer Science, University of Basel, Spiegelgasse 1, 4051 Basel, Switzerland.
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18
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Zheng J, Wheeler E, Pietzner M, Andlauer TFM, Yau MS, Hartley AE, Brumpton BM, Rasheed H, Kemp JP, Frysz M, Robinson J, Reppe S, Prijatelj V, Gautvik KM, Falk L, Maerz W, Gergei I, Peyser PA, Kavousi M, de Vries PS, Miller CL, Bos M, van der Laan SW, Malhotra R, Herrmann M, Scharnagl H, Kleber M, Dedoussis G, Zeggini E, Nethander M, Ohlsson C, Lorentzon M, Wareham N, Langenberg C, Holmes MV, Davey Smith G, Tobias JH. Lowering of Circulating Sclerostin May Increase Risk of Atherosclerosis and Its Risk Factors: Evidence From a Genome-Wide Association Meta-Analysis Followed by Mendelian Randomization. Arthritis Rheumatol 2023; 75:1781-1792. [PMID: 37096546 PMCID: PMC10586470 DOI: 10.1002/art.42538] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Revised: 03/22/2023] [Accepted: 04/18/2023] [Indexed: 04/26/2023]
Abstract
OBJECTIVE In this study, we aimed to establish the causal effects of lowering sclerostin, target of the antiosteoporosis drug romosozumab, on atherosclerosis and its risk factors. METHODS A genome-wide association study meta-analysis was performed of circulating sclerostin levels in 33,961 European individuals. Mendelian randomization (MR) was used to predict the causal effects of sclerostin lowering on 15 atherosclerosis-related diseases and risk factors. RESULTS We found that 18 conditionally independent variants were associated with circulating sclerostin. Of these, 1 cis signal in SOST and 3 trans signals in B4GALNT3, RIN3, and SERPINA1 regions showed directionally opposite signals for sclerostin levels and estimated bone mineral density. Variants with these 4 regions were selected as genetic instruments. MR using 5 correlated cis-SNPs suggested that lower sclerostin increased the risk of type 2 diabetes mellitus (DM) (odds ratio [OR] 1.32 [95% confidence interval (95% CI) 1.03-1.69]) and myocardial infarction (MI) (OR 1.35 [95% CI 1.01-1.79]); sclerostin lowering was also suggested to increase the extent of coronary artery calcification (CAC) (β = 0.24 [95% CI 0.02-0.45]). MR using both cis and trans instruments suggested that lower sclerostin increased hypertension risk (OR 1.09 [95% CI 1.04-1.15]), but otherwise had attenuated effects. CONCLUSION This study provides genetic evidence to suggest that lower levels of sclerostin may increase the risk of hypertension, type 2 DM, MI, and the extent of CAC. Taken together, these findings underscore the requirement for strategies to mitigate potential adverse effects of romosozumab treatment on atherosclerosis and its related risk factors.
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Affiliation(s)
- Jie Zheng
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China, and Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the People's Republic of China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China, and MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of BristolBristolUK
| | - Eleanor Wheeler
- MRC Epidemiology Unit, Institute of Metabolic ScienceUniversity of Cambridge School of Clinical MedicineCambridgeUK
| | - Maik Pietzner
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK, and Computational Medicine, Berlin Institute of Health at Charité–Universitätsmedizin BerlinBerlinGermany
| | - Till F. M. Andlauer
- Department of Neurology, Klinikum rechts der Isar, School of MedicineTechnical University of MunichMunichGermany
| | - Michelle S. Yau
- Marcus Institute for Aging Research, Hebrew SeniorLifeHarvard Medical SchoolBostonMassachusetts
| | | | - Ben Michael Brumpton
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, and HUNT Research Centre, Department of Public Health and Nursing, NTNUNorwegian University of Science and TechnologyLevangerNorway
| | - Humaira Rasheed
- MRC IEU, Bristol Medical School, University of Bristol, Bristol, UK, and HUNT Research Centre, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Levanger, Norway, and Division of Medicine and Laboratory Sciences, Faculty of MedicineUniversity of OsloOsloNorway
| | - John P. Kemp
- MRC IEU, Bristol Medical School, University of Bristol, Bristol, UK, and Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia, and The University of Queensland Diamantina InstituteThe University of QueenslandBrisbaneQueenslandAustralia
| | - Monika Frysz
- MRC IEU, Bristol Medical School, University of Bristol, and Musculoskeletal Research UnitUniversity of BristolBristolUK
| | - Jamie Robinson
- MRC IEU, Bristol Medical SchoolUniversity of BristolBristolUK
| | - Sjur Reppe
- Unger‐Vetlesen Institute, Lovisenberg Diaconal Hospital and Department of Plastic and Reconstructive Surgery, Oslo University Hospital and Department of Medical BiochemistryOslo University HospitalOsloNorway
| | - Vid Prijatelj
- Department of Internal MedicineErasmus MC University Medical CenterRotterdamThe Netherlands
| | | | - Louise Falk
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK, and Computational Medicine, Berlin Institute of Health at Charité–Universitätsmedizin BerlinBerlinGermany
| | - Winfried Maerz
- Clinical Institute of Medical and Chemical Laboratory Diagnostics, Medical University of Graz, Austria, and SYNLAB Academy, SYNLAB Holding Deutschland GmbH and Vth Department of Medicine (Nephrology, Hypertensiology, Rheumatology, Endocrinology, Diabetology), Medical Faculty MannheimUniversity of HeidelbergMannheimGermany
| | - Ingrid Gergei
- Vth Department of Medicine (Nephrology, Hypertensiology, Rheumatology, Endocrinology, Diabetology), Medical Faculty Mannheim, University of Heidelberg, Mannheim, and Therapeutic Area Cardiovascular MedicineBoehringer Ingelheim International GmbHIngelheimGermany
| | - Patricia A. Peyser
- Department of Epidemiology, School of Public HealthUniversity of MichiganAnn Arbor
| | - Maryam Kavousi
- Department of Epidemiology, Erasmus MCUniversity Medical CenterRotterdamThe Netherlands
| | - Paul S. de Vries
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public HealthThe University of Texas Health Science Center at Houston
| | - Clint L. Miller
- Center for Public Health Genomics, Department of Public Health SciencesUniversity of VirginiaCharlottesville
| | - Maxime Bos
- Department of Epidemiology, Erasmus MCUniversity Medical CenterRotterdamThe Netherlands
| | - Sander W. van der Laan
- Central Diagnostics Laboratory, Division of Laboratories, Pharmacy, and Biomedical Genetics, University Medical Center UtrechtUtrecht UniversityUtrechtthe Netherlands
| | - Rajeev Malhotra
- Cardiology Division, Department of MedicineMassachusetts General HospitalBoston
| | - Markus Herrmann
- Clinical Institute of Medical and Chemical Laboratory DiagnosticsMedical University of GrazGrazAustria
| | - Hubert Scharnagl
- Clinical Institute of Medical and Chemical Laboratory DiagnosticsMedical University of GrazGrazAustria
| | - Marcus Kleber
- SYNLAB Academy, SYNLAB Holding Deutschland GmbHMannheimGermany
| | - George Dedoussis
- Department of Nutrition and Dietetics, School of Health Science and EducationHarokopio UniversityAthensGreece
| | - Eleftheria Zeggini
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, and Technical University of Munich (TUM) and Klinikum Rechts der IsarTUM School of MedicineMunichGermany
| | - Maria Nethander
- Sahlgrenska Osteoporosis Centre, Centre for Bone and Arthritis Research, Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, University of Gothenburg and Bioinformatics and Data Centre, Sahlgrenska AcademyUniversity of GothenburgGothenburgSweden
| | - Claes Ohlsson
- Sahlgrenska Osteoporosis Centre, Centre for Bone and Arthritis Research, Department of Internal Medicine and Clinical Nutrition, Institute of MedicineUniversity of GothenburgGothenburgSweden
| | - Mattias Lorentzon
- Sahlgrenska Osteoporosis Centre, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden, and Region Västra Götaland, Geriatric Medicine, Sahlgrenska University Hospital, Mölndal, Sweden, and Mary McKillop Institute for Health ResearchAustralian Catholic UniversityMelbourneVictoriaAustralia
| | - Nick Wareham
- MRC Epidemiology Unit, Institute of Metabolic ScienceUniversity of Cambridge School of Clinical MedicineCambridgeUK
| | - Claudia Langenberg
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK, and Computational Medicine, Berlin Institute of Health at Charité–Universitätsmedizin BerlinBerlinGermany
| | - Michael V. Holmes
- MRC IEU, Bristol Medical School, University of Bristol, and Medical Research Council Population Health Research Unit, University of Oxford, and Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population HealthUniversity of Oxford, and National Institute for Health Research, Oxford Biomedical Research Centre, Oxford University HospitalOxfordUK
| | | | - Jonathan H. Tobias
- MRC IEU, Bristol Medical School, University of Bristol, and Musculoskeletal Research UnitUniversity of BristolBristolUK
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Baylis RA, Gao H, Wang F, Bell CF, Luo L, Björkegren JL, Leeper NJ. Identifying shared transcriptional risk patterns between atherosclerosis and cancer. iScience 2023; 26:107513. [PMID: 37636064 PMCID: PMC10448075 DOI: 10.1016/j.isci.2023.107513] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Revised: 06/18/2023] [Accepted: 07/27/2023] [Indexed: 08/29/2023] Open
Abstract
Cancer and cardiovascular disease (CVD) are the leading causes of death worldwide. Numerous overlapping pathophysiologic mechanisms have been hypothesized to drive the development of both diseases. Further investigation of these common pathways could allow for the identification of mutually detrimental processes and therapeutic targeting to derive mutual benefit. In this study, we intersect transcriptomic datasets correlated with disease severity or patient outcomes for both cancer and atherosclerotic CVD. These analyses confirmed numerous pathways known to underlie both diseases, such as inflammation and hypoxia, but also identified several novel shared pathways. We used these to explore common translational targets by applying the drug prediction software, OCTAD, to identify compounds that simultaneously reverse the gene expression signature for both diseases. These analyses suggest that certain tumor-specific therapeutic approaches may be implemented so that they avoid cardiovascular consequences, and in some cases may even be used to simultaneously target co-prevalent cancer and atherosclerosis.
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Affiliation(s)
- Richard A. Baylis
- Department of Surgery, Division of Vascular Surgery, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Cardiovascular Institute, Stanford, CA, USA
- Department of Medicine, Division of Cardiology, University of California, San Francisco, CA, USA
- Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Hua Gao
- Department of Surgery, Division of Vascular Surgery, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Cardiovascular Institute, Stanford, CA, USA
| | - Fudi Wang
- Department of Surgery, Division of Vascular Surgery, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Cardiovascular Institute, Stanford, CA, USA
| | - Caitlin F. Bell
- Department of Surgery, Division of Vascular Surgery, Stanford University School of Medicine, Stanford, CA, USA
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Lingfeng Luo
- Department of Surgery, Division of Vascular Surgery, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Cardiovascular Institute, Stanford, CA, USA
| | - Johan L.M. Björkegren
- Department of Medicine, Karolinska Institute, Huddinge, Sweden
- Department of Genetics and Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Nicholas J. Leeper
- Department of Surgery, Division of Vascular Surgery, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Cardiovascular Institute, Stanford, CA, USA
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, USA
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20
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Quaye LNK, Dalzell CE, Deloukas P, Smith AJP. The Genetics of Coronary Artery Disease: A Vascular Perspective. Cells 2023; 12:2232. [PMID: 37759455 PMCID: PMC10527262 DOI: 10.3390/cells12182232] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Revised: 08/31/2023] [Accepted: 09/01/2023] [Indexed: 09/29/2023] Open
Abstract
Genome-wide association studies (GWAS) have identified a large number of genetic loci for coronary artery disease (CAD), with many located close to genes associated with traditional CAD risk pathways, such as lipid metabolism and inflammation. It is becoming evident with recent CAD GWAS meta-analyses that vascular pathways are also highly enriched and present an opportunity for novel therapeutics. This review examines GWAS-enriched vascular gene loci, the pathways involved and their potential role in CAD pathogenesis. The functionality of variants is explored from expression quantitative trait loci, massively parallel reporter assays and CRISPR-based gene-editing tools. We discuss how this research may lead to novel therapeutic tools to treat cardiovascular disorders.
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Affiliation(s)
| | | | - Panos Deloukas
- William Harvey Research Institute, Faculty of Medicine and Dentistry, Queen Mary University of London, London EC1M 6BQ, UK; (L.N.K.Q.); (C.E.D.); (A.J.P.S.)
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21
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Su C, Xu Z, Shan X, Cai B, Zhao H, Zhang J. Cell-type-specific co-expression inference from single cell RNA-sequencing data. Nat Commun 2023; 14:4846. [PMID: 37563115 PMCID: PMC10415381 DOI: 10.1038/s41467-023-40503-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Accepted: 07/28/2023] [Indexed: 08/12/2023] Open
Abstract
The advancement of single cell RNA-sequencing (scRNA-seq) technology has enabled the direct inference of co-expressions in specific cell types, facilitating our understanding of cell-type-specific biological functions. For this task, the high sequencing depth variations and measurement errors in scRNA-seq data present two significant challenges, and they have not been adequately addressed by existing methods. We propose a statistical approach, CS-CORE, for estimating and testing cell-type-specific co-expressions, that explicitly models sequencing depth variations and measurement errors in scRNA-seq data. Systematic evaluations show that most existing methods suffered from inflated false positives as well as biased co-expression estimates and clustering analysis, whereas CS-CORE gave accurate estimates in these experiments. When applied to scRNA-seq data from postmortem brain samples from Alzheimer's disease patients/controls and blood samples from COVID-19 patients/controls, CS-CORE identified cell-type-specific co-expressions and differential co-expressions that were more reproducible and/or more enriched for relevant biological pathways than those inferred from existing methods.
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Affiliation(s)
- Chang Su
- Department of Biostatistics, Yale University, New Haven, CT, USA
- Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA, USA
| | - Zichun Xu
- Department of Biostatistics, Yale University, New Haven, CT, USA
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Xinning Shan
- Department of Biostatistics, Yale University, New Haven, CT, USA
| | - Biao Cai
- Department of Biostatistics, Yale University, New Haven, CT, USA
- Department of Mathematical Sciences, University of Cincinnati, Cincinnati, OH, USA
| | - Hongyu Zhao
- Department of Biostatistics, Yale University, New Haven, CT, USA.
| | - Jingfei Zhang
- Information Systems and Operations Management, Emory University, Atlanta, GA, USA.
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22
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Yin M, Xu W, Pang J, Xie S, Xiang M, Shi B, Fan H, Yu G. Causal relationship between osteoarthritis with atrial fibrillation and coronary atherosclerosis: a bidirectional Mendelian randomization study of European ancestry. Front Cardiovasc Med 2023; 10:1213672. [PMID: 37583579 PMCID: PMC10424699 DOI: 10.3389/fcvm.2023.1213672] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Accepted: 07/20/2023] [Indexed: 08/17/2023] Open
Abstract
Background Osteoarthritis (OA) is a degenerative disease with high prevalence. Some observational studies have shown that patients with osteoarthritis often have co-existing cardiovascular diseases (CVD) such as atrial fibrillation (AF) and coronary atherosclerosis (CA). However, there is still a lack of stronger evidence confirming the association between osteoarthritis and cardiovascular disease. In this study, we used a bidirectional two-sample Mendelian randomization study to investigate the relationship between OA with AF and CA. Methods OA data from the UK Biobank and arcOGEN (Arthritis Research UK Osteoarthritis Genetics, a study that aimed to find genetic determinants of osteoarthritis and elucidate the genetic architecture of the disease) integration were selected for the study (n = 417,596), AF data were obtained from six studies (n = 1,030,836), and coronary atherosclerosis data were derived from the FinnGen (n = 218,792). MR analysis was performed primarily using the Inverse variance weighted (IVW) method, with MR Egger, weighted median, simple mode, weighted mode as supplements, sensitivity analysis was performed using Cochran Q statistic, and leave-one-out analysis. Results We found that OA and AF were positively associated [IVW: OR (95% CI): 1.11 (1.04, 1.19), P = 0.002], while OA and CA were negatively associated [IVW: OR (95% CI): 0.88 (0.79, 0.98), P = 0.02]. In the reverse MR analysis, no effect of AF on OA was found [IVW: OR (95% CI): 1.00 (0.97, 1.03), P = 0.84], meanwhile, CA and OA were found to be associated negatively [IVW: OR (95% CI): 0.95 (0.92, 0.99), P = 0.01]. No violations of MR assumptions were found in the sensitivity analysis. Conclusion This research confirms that OA is a risk factor for AF, and there is a mutual protective factor between OA and CA. However, further studies are still necessary to elucidate the underlying mechanisms.
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Affiliation(s)
- Meng Yin
- Shandong Academy of Occupational Health and Occupational Medicine, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, China
| | - Wenchang Xu
- School of Acupuncture and Tuina, Shandong University of Traditional Chinese Medicine, Jinan, China
- Neck-Shoulder and Lumbocrural Pain Hospital of Shandong First Medical University, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, China
| | - Jixiang Pang
- Department of Development Planning and Discipline Construction, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, China
| | - Siwen Xie
- Shandong Academy of Occupational Health and Occupational Medicine, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, China
| | - Mengting Xiang
- Shandong Academy of Occupational Health and Occupational Medicine, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, China
| | - Bin Shi
- Neck-Shoulder and Lumbocrural Pain Hospital of Shandong First Medical University, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, China
| | - Hua Fan
- Department of Development Planning and Discipline Construction, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, China
| | - Gongchang Yu
- Neck-Shoulder and Lumbocrural Pain Hospital of Shandong First Medical University, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, China
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23
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von Scheidt M, Bauer S, Ma A, Hao K, Kessler T, Vilne B, Wang Y, Hodonsky CJ, Ghosh SK, Mokry M, Gao H, Kawai K, Sakamoto A, Kaiser J, Bongiovanni D, Fleig J, Oldenbuettel L, Chen Z, Moggio A, Sager HB, Hecker JS, Bassermann F, Maegdefessel L, Miller CL, Koenig W, Zeiher AM, Dimmeler S, Graw M, Braun C, Ruusalepp A, Leeper NJ, Kovacic JC, Björkegren JL, Schunkert H. Leukocytes carrying Clonal Hematopoiesis of Indeterminate Potential (CHIP) Mutations invade Human Atherosclerotic Plaques. medRxiv 2023:2023.07.22.23292754. [PMID: 37546840 PMCID: PMC10402238 DOI: 10.1101/2023.07.22.23292754] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
Background Leukocyte progenitors derived from clonal hematopoiesis of undetermined potential (CHIP) are associated with increased cardiovascular events. However, the prevalence and functional relevance of CHIP in coronary artery disease (CAD) are unclear, and cells affected by CHIP have not been detected in human atherosclerotic plaques. Methods CHIP mutations in blood and tissues were identified by targeted deep-DNA-sequencing (DNAseq: coverage >3,000) and whole-genome-sequencing (WGS: coverage >35). CHIP-mutated leukocytes were visualized in human atherosclerotic plaques by mutaFISH™. Functional relevance of CHIP mutations was studied by RNAseq. Results DNAseq of whole blood from 540 deceased CAD patients of the Munich cardIovaScular StudIes biObaNk (MISSION) identified 253 (46.9%) CHIP mutation carriers (mean age 78.3 years). DNAseq on myocardium, atherosclerotic coronary and carotid arteries detected identical CHIP mutations in 18 out of 25 mutation carriers in tissue DNA. MutaFISH™ visualized individual macrophages carrying DNMT3A CHIP mutations in human atherosclerotic plaques. Studying monocyte-derived macrophages from Stockholm-Tartu Atherosclerosis Reverse Networks Engineering Task (STARNET; n=941) by WGS revealed CHIP mutations in 14.2% (mean age 67.1 years). RNAseq of these macrophages revealed that expression patterns in CHIP mutation carriers differed substantially from those of non-carriers. Moreover, patterns were different depending on the underlying mutations, e.g. those carrying TET2 mutations predominantly displayed upregulated inflammatory signaling whereas ASXL1 mutations showed stronger effects on metabolic pathways. Conclusions Deep-DNA-sequencing reveals a high prevalence of CHIP mutations in whole blood of CAD patients. CHIP-affected leukocytes invade plaques in human coronary arteries. RNAseq data obtained from macrophages of CHIP-affected patients suggest that pro-atherosclerotic signaling differs depending on the underlying mutations. Further studies are necessary to understand whether specific pathways affected by CHIP mutations may be targeted for personalized treatment.
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Affiliation(s)
- Moritz von Scheidt
- Department of Cardiology, German Heart Center Munich, Technical University Munich, Munich, Germany
- Deutsches Zentrum für Herz- und Kreislaufforschung (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Sabine Bauer
- Department of Cardiology, German Heart Center Munich, Technical University Munich, Munich, Germany
- Deutsches Zentrum für Herz- und Kreislaufforschung (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Angela Ma
- Department of Genetics and Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Ke Hao
- Department of Genetics and Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Thorsten Kessler
- Department of Cardiology, German Heart Center Munich, Technical University Munich, Munich, Germany
- Deutsches Zentrum für Herz- und Kreislaufforschung (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Baiba Vilne
- Deutsches Zentrum für Herz- und Kreislaufforschung (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
- Bioinformatics Lab, Riga Stradiņš University, Riga, Latvia
- SIA Net-OMICS, Riga, Latvia
| | - Ying Wang
- Department of Pathology and Laboratory Medicine, Centre for Heart Lung Innovation, University of British Columbia, Vancouver, Canada
| | - Chani J. Hodonsky
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | | | - Michal Mokry
- Laboratory of Experimental Cardiology, Department of Cardiology, University Medical Center Utrecht, University Utrecht, Utrecht, Netherlands
- Central Diagnostics Laboratory, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Hua Gao
- Division of Vascular Surgery, Department of Surgery, Stanford University School of Medicine, Stanford, USA
| | | | - Atsushi Sakamoto
- CVPath Institute, Inc, Gaithersburg, USA
- Division of Cardiology, Internal Medicine III, Hamamatsu University School of Medicine, Hamamatsu, Japan
| | - Juliane Kaiser
- Institute of Legal Medicine, Faculty of Medicine, LMU Munich, Germany
| | - Dario Bongiovanni
- Department of Internal Medicine I, Cardiology, University Hospital Augsburg, University of Augsburg, Germany
- Department of Cardiovascular Medicine, Humanitas Clinical and Research Center IRCCS and Humanitas University, Rozzano, Milan, Italy
| | - Julia Fleig
- Department of Cardiology, German Heart Center Munich, Technical University Munich, Munich, Germany
| | - Lilith Oldenbuettel
- Department of Cardiology, German Heart Center Munich, Technical University Munich, Munich, Germany
| | - Zhifen Chen
- Department of Cardiology, German Heart Center Munich, Technical University Munich, Munich, Germany
- Deutsches Zentrum für Herz- und Kreislaufforschung (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Aldo Moggio
- Department of Cardiology, German Heart Center Munich, Technical University Munich, Munich, Germany
- Deutsches Zentrum für Herz- und Kreislaufforschung (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Hendrik B. Sager
- Department of Cardiology, German Heart Center Munich, Technical University Munich, Munich, Germany
- Deutsches Zentrum für Herz- und Kreislaufforschung (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Judith S. Hecker
- Department of Medicine III, Technical University of Munich (TUM), Klinikum rechts der Isar, Munich, Germany
| | - Florian Bassermann
- Department of Medicine III, Technical University of Munich (TUM), Klinikum rechts der Isar, Munich, Germany
| | - Lars Maegdefessel
- Deutsches Zentrum für Herz- und Kreislaufforschung (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
- Department for Vascular and Endovascular Surgery, Klinikum Rechts der Isar, Technical University Munich, Munich, Germany
| | - Clint L. Miller
- Center for Public Health Genomics, Department of Public Health Sciences, Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA, USA
| | - Wolfgang Koenig
- Department of Cardiology, German Heart Center Munich, Technical University Munich, Munich, Germany
- Deutsches Zentrum für Herz- und Kreislaufforschung (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Andreas M. Zeiher
- Institute for Cardiovascular Regeneration, Goethe University Frankfurt am Main, Frankfurt am Main, Germany
| | - Stefanie Dimmeler
- Institute for Cardiovascular Regeneration, Goethe University Frankfurt am Main, Frankfurt am Main, Germany
| | - Matthias Graw
- Institute of Legal Medicine, Faculty of Medicine, LMU Munich, Germany
| | - Christian Braun
- Institute of Legal Medicine, Faculty of Medicine, LMU Munich, Germany
| | - Arno Ruusalepp
- Department of Cardiac Surgery, The Heart Clinic, Tartu University Hospital, Tartu, Estonia
- Clinical Gene Networks AB, Stockholm, Sweden
- Institute of Clinical Medicine, Faculty of Medicine, Tartu University, Tartu, Estonia
| | - Nicholas J. Leeper
- Central Diagnostics Laboratory, University Medical Center Utrecht, Utrecht, The Netherlands
- Stanford Cardiovascular Institute, Stanford University, Stanford, USA
| | - Jason C. Kovacic
- Victor Chang Cardiac Research Institute, Darlinghurst, Australia
- St. Vincent’s Clinical School, University of New South Wales, Sydney, Australia
- Cardiovascular Research Institute, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Johan L.M. Björkegren
- Department of Genetics and Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, USA
- Clinical Gene Networks AB, Stockholm, Sweden
- Department of Medicine, Huddinge, Karolinska Institutet, Karolinska Universitetssjukhuset, Stockholm, Sweden
| | - Heribert Schunkert
- Department of Cardiology, German Heart Center Munich, Technical University Munich, Munich, Germany
- Deutsches Zentrum für Herz- und Kreislaufforschung (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
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Zhang Y, Wang X, Li XK, Lv SJ, Wang HP, Liu Y, Zhou J, Gong H, Chen XF, Ren SC, Zhang H, Dai Y, Cai H, Yan B, Chen HZ, Tang X. Sirtuin 2 deficiency aggravates ageing-induced vascular remodelling in humans and mice. Eur Heart J 2023:ehad381. [PMID: 37377116 PMCID: PMC10393077 DOI: 10.1093/eurheartj/ehad381] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/09/2022] [Revised: 04/21/2023] [Accepted: 05/09/2023] [Indexed: 06/29/2023] Open
Abstract
AIMS The mechanisms underlying ageing-induced vascular remodelling remain unclear. This study investigates the role and underlying mechanisms of the cytoplasmic deacetylase sirtuin 2 (SIRT2) in ageing-induced vascular remodelling. METHODS AND RESULTS Transcriptome and quantitative real-time PCR data were used to analyse sirtuin expression. Young and old wild-type and Sirt2 knockout mice were used to explore vascular function and pathological remodelling. RNA-seq, histochemical staining, and biochemical assays were used to evaluate the effects of Sirt2 knockout on the vascular transcriptome and pathological remodelling and explore the underlying biochemical mechanisms. Among the sirtuins, SIRT2 had the highest levels in human and mouse aortas. Sirtuin 2 activity was reduced in aged aortas, and loss of SIRT2 accelerated vascular ageing. In old mice, SIRT2 deficiency aggravated ageing-induced arterial stiffness and constriction-relaxation dysfunction, accompanied by aortic remodelling (thickened vascular medial layers, breakage of elastin fibres, collagen deposition, and inflammation). Transcriptome and biochemical analyses revealed that the ageing-controlling protein p66Shc and metabolism of mitochondrial reactive oxygen species (mROS) contributed to SIRT2 function in vascular ageing. Sirtuin 2 repressed p66Shc activation and mROS production by deacetylating p66Shc at lysine 81. Elimination of reactive oxygen species by MnTBAP repressed the SIRT2 deficiency-mediated aggravation of vascular remodelling and dysfunction in angiotensin II-challenged and aged mice. The SIRT2 coexpression module in aortas was reduced with ageing across species and was a significant predictor of age-related aortic diseases in humans. CONCLUSION The deacetylase SIRT2 is a response to ageing that delays vascular ageing, and the cytoplasm-mitochondria axis (SIRT2-p66Shc-mROS) is important for vascular ageing. Therefore, SIRT2 may serve as a potential therapeutic target for vascular rejuvenation.
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Affiliation(s)
- Yang Zhang
- Department of Biochemistry & Molecular Biology, State Key Laboratory of Common Mechanism Research for Major Diseases, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & Peking Union Medical College, 5 Dong Dan San Tiao, Beijing 100005, China
| | - Xiaoman Wang
- Department of Biochemistry & Molecular Biology, State Key Laboratory of Common Mechanism Research for Major Diseases, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & Peking Union Medical College, 5 Dong Dan San Tiao, Beijing 100005, China
| | - Xun-Kai Li
- Department of Biochemistry & Molecular Biology, State Key Laboratory of Common Mechanism Research for Major Diseases, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & Peking Union Medical College, 5 Dong Dan San Tiao, Beijing 100005, China
| | - Shuang-Jie Lv
- Department of Biochemistry & Molecular Biology, State Key Laboratory of Common Mechanism Research for Major Diseases, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & Peking Union Medical College, 5 Dong Dan San Tiao, Beijing 100005, China
| | - He-Ping Wang
- Department of Biochemistry & Molecular Biology, State Key Laboratory of Common Mechanism Research for Major Diseases, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & Peking Union Medical College, 5 Dong Dan San Tiao, Beijing 100005, China
| | - Yang Liu
- Key Laboratory of Birth Defects and Related Diseases of Women and Children of MOE, State Key Laboratory of Biotherapy, West China Second University Hospital, Sichuan University, No.17 People's South Road, Chengdu, Sichuan 610041, China
- Division of Vascular Surgery, Department of General Surgery, and Laboratory of Cardiovascular Diseases, West China Hospital, Sichuan University, No.17 People's South Road, Chengdu, Sichuan 610041, China
| | - Jingyue Zhou
- Key Laboratory of Birth Defects and Related Diseases of Women and Children of MOE, State Key Laboratory of Biotherapy, West China Second University Hospital, Sichuan University, No.17 People's South Road, Chengdu, Sichuan 610041, China
- National Health Commission Key Laboratory of Chronobiology, Sichuan University, No.17 People's South Road, Chengdu, Sichuan 610041, China
- Development and Related Diseases of Women and Children, Key Laboratory of Sichuan Province, West China Second University Hospital, Sichuan University, No.17 People's South Road, Chengdu, Sichuan 610041, China
| | - Hui Gong
- Key Laboratory of Birth Defects and Related Diseases of Women and Children of MOE, State Key Laboratory of Biotherapy, West China Second University Hospital, Sichuan University, No.17 People's South Road, Chengdu, Sichuan 610041, China
- National Clinical Research Center for Geriatrics, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, No.17 People's South Road, Chengdu, Sichuan 610041, China
| | - Xiao-Feng Chen
- School of Basic Medical Sciences, Chengdu University of Traditional Chinese Medicine, 1166 Liutai Avenue, Chengdu, Sichuan 611137, China
| | - Si-Chong Ren
- Department of Nephrology, First Affiliated Hospital of Chengdu Medical College, 783 Xindu Avenue, Chengdu, Sichuan 610500, China
| | - Huina Zhang
- Beijing Institute of Heart Lung and Blood Vessel Diseases, Beijing Anzhen Hospital, Capital Medical University, No. 2 Anzhen Road, Beijing 10029, China
| | - Yuxiang Dai
- Department of Cardiology, Zhongshan Hospital, Fudan University, Shanghai Institute of Cardiovascular Diseases, National Clinical Research Center for Interventional Medicine, 180 Fenglin Road, Shanghai 200032, China
| | - Hua Cai
- Division of Molecular Medicine, Department of Anesthesiology, David Geffen School of Medicine at University of California Los Angeles, Los Angeles, CA 90095, USA
- Division of Cardiology, Department of Medicine, David Geffen School of Medicine at University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Bo Yan
- Institute of Precision Medicine, Jining Medical University, 133 Hehua Road, Taibaihu New District, Jining, Shandong 272067, China
| | - Hou-Zao Chen
- Department of Biochemistry & Molecular Biology, State Key Laboratory of Common Mechanism Research for Major Diseases, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & Peking Union Medical College, 5 Dong Dan San Tiao, Beijing 100005, China
- Medical Epigenetics Research Center, Chinese Academy of Medical Sciences, 5 Dong Dan San Tiao, Beijing 100005, China
| | - Xiaoqiang Tang
- Key Laboratory of Birth Defects and Related Diseases of Women and Children of MOE, State Key Laboratory of Biotherapy, West China Second University Hospital, Sichuan University, No.17 People's South Road, Chengdu, Sichuan 610041, China
- National Health Commission Key Laboratory of Chronobiology, Sichuan University, No.17 People's South Road, Chengdu, Sichuan 610041, China
- Development and Related Diseases of Women and Children, Key Laboratory of Sichuan Province, West China Second University Hospital, Sichuan University, No.17 People's South Road, Chengdu, Sichuan 610041, China
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López Rodríguez M, Arasu UT, Kaikkonen MU. Exploring the genetic basis of coronary artery disease using functional genomics. Atherosclerosis 2023; 374:87-98. [PMID: 36801133 DOI: 10.1016/j.atherosclerosis.2023.01.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Revised: 01/20/2023] [Accepted: 01/24/2023] [Indexed: 02/05/2023]
Abstract
Genome-wide Association Studies (GWAS) have identified more than 300 loci associated with coronary artery disease (CAD), defining the genetic risk map of the disease. However, the translation of the association signals into biological-pathophysiological mechanisms constitute a major challenge. Through a group of examples of studies focused on CAD, we discuss the rationale, basic principles and outcomes of the main methodologies implemented to prioritize and characterize causal variants and their target genes. Additionally, we highlight the strategies as well as the current methods that integrate association and functional genomics data to dissect the cellular specificity underlying the complexity of disease mechanisms. Despite the limitations of existing approaches, the increasing knowledge generated through functional studies helps interpret GWAS maps and opens novel avenues for the clinical usability of association data.
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Affiliation(s)
- Maykel López Rodríguez
- A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, 70211, Finland; Department of Pathology and Laboratory Medicine, University of California, UCLA, Los Angeles, USA.
| | - Uma Thanigai Arasu
- A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, 70211, Finland
| | - Minna U Kaikkonen
- A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, 70211, Finland.
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26
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Gupta RM, Schnitzler GR, Fang S, Lee-Kim VS, Barry A. Multiomic Analysis and CRISPR Perturbation Screens Identify Endothelial Cell Programs and Novel Therapeutic Targets for Coronary Artery Disease. Arterioscler Thromb Vasc Biol 2023; 43:600-608. [PMID: 36994731 PMCID: PMC10170398 DOI: 10.1161/atvbaha.123.318328] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Accepted: 03/01/2023] [Indexed: 03/31/2023]
Abstract
Endothelial cells (EC) are an important mediator of atherosclerosis and vascular disease. Their exposure to atherogenic risk factors such as hypertension and serum cholesterol leads to endothelial dysfunction and many disease-associated processes. Identifying which of these multiple EC functions is causally related to disease risk has been challenging. There is evidence from in vivo models and human sequencing studies that dysregulation of nitric oxide production directly affects risk of coronary artery disease. Human genetics can help prioritize the other EC functions with causal relationships because germline mutations are acquired at birth and serve as a randomized test of which pathways affect disease risk. Though several coronary artery disease risk variants have been linked to EC function, this process has been slow and laborious. Unbiased analyses of EC dysfunction using multiomic approaches promise to identify the causal genetic mechanisms responsible for vascular disease. Here, we review the data from genomic, epigenomic, and transcriptomic studies that prioritize EC-specific causal pathways. New methods that CRISPR (clustered regularly interspaced short palindromic repeats) perturbation technology with genomic, epigenomic, and transcriptomic analysis promise to speed up the characterization of disease-associated genetic variation. We summarize several recent studies in ECs which use high-throughput genetic perturbation to identify disease-relevant pathways and novel mechanisms of disease. These genetically validated pathways can accelerate the identification of drug targets for the prevention and treatment of atherosclerosis.
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Affiliation(s)
- Rajat M Gupta
- Divisions of Genetics and Cardiology, Department of Medicine, Brigham and Women's Hospital, Boston MA (R.M.G., G.R.S., S.F., V.S.L.-K., A.B.)
- Broad Institute of MIT and Harvard, Cambridge, MA (R.M.G., G.R.S., S.F., V.S.L.-K., A.B.)
| | - Gavin R Schnitzler
- Divisions of Genetics and Cardiology, Department of Medicine, Brigham and Women's Hospital, Boston MA (R.M.G., G.R.S., S.F., V.S.L.-K., A.B.)
- Broad Institute of MIT and Harvard, Cambridge, MA (R.M.G., G.R.S., S.F., V.S.L.-K., A.B.)
| | - Shi Fang
- Divisions of Genetics and Cardiology, Department of Medicine, Brigham and Women's Hospital, Boston MA (R.M.G., G.R.S., S.F., V.S.L.-K., A.B.)
- Broad Institute of MIT and Harvard, Cambridge, MA (R.M.G., G.R.S., S.F., V.S.L.-K., A.B.)
| | - Vivian S Lee-Kim
- Divisions of Genetics and Cardiology, Department of Medicine, Brigham and Women's Hospital, Boston MA (R.M.G., G.R.S., S.F., V.S.L.-K., A.B.)
- Broad Institute of MIT and Harvard, Cambridge, MA (R.M.G., G.R.S., S.F., V.S.L.-K., A.B.)
| | - Aurelie Barry
- Divisions of Genetics and Cardiology, Department of Medicine, Brigham and Women's Hospital, Boston MA (R.M.G., G.R.S., S.F., V.S.L.-K., A.B.)
- Broad Institute of MIT and Harvard, Cambridge, MA (R.M.G., G.R.S., S.F., V.S.L.-K., A.B.)
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Wong D, Auguste G, Cardenas CLL, Turner AW, Chen Y, Song Y, Ma L, Perry RN, Aherrahrou R, Kuppusamy M, Yang C, Mosquera JV, Dube CJ, Khan MD, Palmore M, Kalra JK, Kavousi M, Peyser PA, Matic L, Hedin U, Manichaikul A, Sonkusare SK, Civelek M, Kovacic JC, Björkegren JL, Malhotra R, Miller CL. FHL5 Controls Vascular Disease-Associated Gene Programs in Smooth Muscle Cells. Circ Res 2023; 132:1144-1161. [PMID: 37017084 PMCID: PMC10147587 DOI: 10.1161/circresaha.122.321692] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Accepted: 03/21/2023] [Indexed: 04/06/2023]
Abstract
BACKGROUND Genome-wide association studies have identified hundreds of loci associated with common vascular diseases, such as coronary artery disease, myocardial infarction, and hypertension. However, the lack of mechanistic insights for many GWAS loci limits their translation into the clinic. Among these loci with unknown functions is UFL1-four-and-a-half LIM (LIN-11, Isl-1, MEC-3) domain 5 (FHL5; chr6q16.1), which reached genome-wide significance in a recent coronary artery disease/ myocardial infarction GWAS meta-analysis. UFL1-FHL5 is also associated with several vascular diseases, consistent with the widespread pleiotropy observed for GWAS loci. METHODS We apply a multimodal approach leveraging statistical fine-mapping, epigenomic profiling, and ex vivo analysis of human coronary artery tissues to implicate FHL5 as the top candidate causal gene. We unravel the molecular mechanisms of the cross-phenotype genetic associations through in vitro functional analyses and epigenomic profiling experiments in coronary artery smooth muscle cells. RESULTS We prioritized FHL5 as the top candidate causal gene at the UFL1-FHL5 locus through expression quantitative trait locus colocalization methods. FHL5 gene expression was enriched in the smooth muscle cells and pericyte population in human artery tissues with coexpression network analyses supporting a functional role in regulating smooth muscle cell contraction. Unexpectedly, under procalcifying conditions, FHL5 overexpression promoted vascular calcification and dysregulated processes related to extracellular matrix organization and calcium handling. Lastly, by mapping FHL5 binding sites and inferring FHL5 target gene function using artery tissue gene regulatory network analyses, we highlight regulatory interactions between FHL5 and downstream coronary artery disease/myocardial infarction loci, such as FOXL1 and FN1 that have roles in vascular remodeling. CONCLUSIONS Taken together, these studies provide mechanistic insights into the pleiotropic genetic associations of UFL1-FHL5. We show that FHL5 mediates vascular disease risk through transcriptional regulation of downstream vascular remodeling gene programs. These transacting mechanisms may explain a portion of the heritable risk for complex vascular diseases.
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Affiliation(s)
- Doris Wong
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, Virginia, USA
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
- Robert M. Berne Cardiovascular Research Center, University of Virginia, Charlottesville, Virginia, USA
| | - Gaëlle Auguste
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
| | - Christian L. Lino Cardenas
- Cardiovascular Research Center, Cardiology Division, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Adam W. Turner
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
| | - Yixuan Chen
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
| | - Yipei Song
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
| | - Lijiang Ma
- Department of Genetics and Genomic Sciences, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, USA
| | - R. Noah Perry
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
- Robert M. Berne Cardiovascular Research Center, University of Virginia, Charlottesville, Virginia, USA
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA
| | - Redouane Aherrahrou
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
| | - Maniselvan Kuppusamy
- Robert M. Berne Cardiovascular Research Center, University of Virginia, Charlottesville, Virginia, USA
| | - Chaojie Yang
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, Virginia, USA
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
| | - Jose Verdezoto Mosquera
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, Virginia, USA
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
| | - Collin J. Dube
- Department of Microbiology, Immunology, and Cancer Biology, University of Virginia, Charlottesville, Virginia, USA
| | - Mohammad Daud Khan
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
| | - Meredith Palmore
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
| | - Jaspreet K. Kalra
- Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, Virginia, USA
| | - Maryam Kavousi
- Department of Epidemiology, Erasmus University Medical Center, The Netherlands
| | | | - Ljubica Matic
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
| | - Ulf Hedin
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
| | - Ani Manichaikul
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, Virginia, USA
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
- Department of Public Health Sciences, University of Virginia, Charlottesville, Virginia, USA
| | - Swapnil K. Sonkusare
- Robert M. Berne Cardiovascular Research Center, University of Virginia, Charlottesville, Virginia, USA
- Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, Virginia, USA
| | - Mete Civelek
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
- Robert M. Berne Cardiovascular Research Center, University of Virginia, Charlottesville, Virginia, USA
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA
| | - Jason C. Kovacic
- Cardiovascular Research Institute, Icahn School of Medicine at Mount Sinai, New York, USA
- Victor Chang Cardiac Research Institute, Darlinghurst, New South Wales, Australia
- St. Vincent’s Clinical School, University of New South Wales, Sydney, Australia
| | - Johan L.M. Björkegren
- Department of Genetics and Genomic Sciences, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, USA
- Integrated Cardio Metabolic Centre, Department of Medicine, Karolinska Institutet, Huddinge, Sweden
| | - Rajeev Malhotra
- Cardiovascular Research Center, Cardiology Division, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Clint L. Miller
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, Virginia, USA
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
- Robert M. Berne Cardiovascular Research Center, University of Virginia, Charlottesville, Virginia, USA
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
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Scarpa JR, Elemento O. Multi-omic molecular profiling and network biology for precision anaesthesiology: a narrative review. Br J Anaesth 2023:S0007-0912(23)00125-3. [PMID: 37055274 DOI: 10.1016/j.bja.2023.03.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Revised: 02/21/2023] [Accepted: 03/04/2023] [Indexed: 04/15/2023] Open
Abstract
Technological advancement, data democratisation, and decreasing costs have led to a revolution in molecular biology in which the entire set of DNA, RNA, proteins, and various other molecules - the 'multi-omic' profile - can be measured in humans. Sequencing 1 million bases of human DNA now costs US$0.01, and emerging technologies soon promise to reduce the cost of sequencing the whole genome to US$100. These trends have made it feasible to sample the multi-omic profile of millions of people, much of which is publicly available for medical research. Can anaesthesiologists use these data to improve patient care? This narrative review brings together a rapidly growing literature in multi-omic profiling across numerous fields that points to the future of precision anaesthesiology. Here, we discuss how DNA, RNA, proteins, and other molecules interact in molecular networks that can be used for preoperative risk stratification, intraoperative optimisation, and postoperative monitoring. This literature provides evidence for four fundamental insights: (1) Clinically similar patients have different molecular profiles and, as a consequence, different outcomes. (2) Vast, publicly available, and rapidly growing molecular datasets have been generated in chronic disease patients and can be repurposed to estimate perioperative risk. (3) Multi-omic networks are altered in the perioperative period and influence postoperative outcomes. (4) Multi-omic networks can serve as empirical, molecular measurements of a successful postoperative course. With this burgeoning universe of molecular data, the anaesthesiologist-of-the-future will tailor their clinical management to an individual's multi-omic profile to optimise postoperative outcomes and long-term health.
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Affiliation(s)
- Joseph R Scarpa
- Department of Anesthesiology, Weill Cornell Medicine, New York, NY, USA.
| | - Olivier Elemento
- Caryl and Israel Englander Institute for Precision Medicine, Weill Cornell Medicine, Cornell University, New York, NY, USA
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29
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Jurrjens AW, Seldin MM, Giles C, Meikle PJ, Drew BG, Calkin AC. The potential of integrating human and mouse discovery platforms to advance our understanding of cardiometabolic diseases. eLife 2023; 12:e86139. [PMID: 37000167 PMCID: PMC10065800 DOI: 10.7554/elife.86139] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Accepted: 03/15/2023] [Indexed: 04/01/2023] Open
Abstract
Cardiometabolic diseases encompass a range of interrelated conditions that arise from underlying metabolic perturbations precipitated by genetic, environmental, and lifestyle factors. While obesity, dyslipidaemia, smoking, and insulin resistance are major risk factors for cardiometabolic diseases, individuals still present in the absence of such traditional risk factors, making it difficult to determine those at greatest risk of disease. Thus, it is crucial to elucidate the genetic, environmental, and molecular underpinnings to better understand, diagnose, and treat cardiometabolic diseases. Much of this information can be garnered using systems genetics, which takes population-based approaches to investigate how genetic variance contributes to complex traits. Despite the important advances made by human genome-wide association studies (GWAS) in this space, corroboration of these findings has been hampered by limitations including the inability to control environmental influence, limited access to pertinent metabolic tissues, and often, poor classification of diseases or phenotypes. A complementary approach to human GWAS is the utilisation of model systems such as genetically diverse mouse panels to study natural genetic and phenotypic variation in a controlled environment. Here, we review mouse genetic reference panels and the opportunities they provide for the study of cardiometabolic diseases and related traits. We discuss how the post-GWAS era has prompted a shift in focus from discovery of novel genetic variants to understanding gene function. Finally, we highlight key advantages and challenges of integrating complementary genetic and multi-omics data from human and mouse populations to advance biological discovery.
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Affiliation(s)
- Aaron W Jurrjens
- Baker Heart and Diabetes Institute, Melbourne, Australia
- Central Clinical School, Monash University, Melbourne, Australia
| | - Marcus M Seldin
- Department of Biological Chemistry and Center for Epigenetics and Metabolism, University of California, Irvine, Irvine, United States
| | - Corey Giles
- Baker Heart and Diabetes Institute, Melbourne, Australia
- Baker Department of Cardiometabolic Health, University of Melbourne, Melbourne, Australia
- Baker Department of Cardiovascular Research Translation and Implementation, La Trobe University, Bundoora, Australia
| | - Peter J Meikle
- Baker Heart and Diabetes Institute, Melbourne, Australia
- Central Clinical School, Monash University, Melbourne, Australia
- Baker Department of Cardiometabolic Health, University of Melbourne, Melbourne, Australia
- Baker Department of Cardiovascular Research Translation and Implementation, La Trobe University, Bundoora, Australia
| | - Brian G Drew
- Baker Heart and Diabetes Institute, Melbourne, Australia
- Central Clinical School, Monash University, Melbourne, Australia
- Baker Department of Cardiometabolic Health, University of Melbourne, Melbourne, Australia
| | - Anna C Calkin
- Baker Heart and Diabetes Institute, Melbourne, Australia
- Central Clinical School, Monash University, Melbourne, Australia
- Baker Department of Cardiometabolic Health, University of Melbourne, Melbourne, Australia
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30
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Clifford BL, Jarrett KE, Cheng J, Cheng A, Seldin M, Morand P, Lee R, Chen M, Baldan A, de Aguiar Vallim TQ, Tarling EJ. RNF130 Regulates LDLR Availability and Plasma LDL Cholesterol Levels. Circ Res 2023; 132:849-863. [PMID: 36876496 PMCID: PMC10065965 DOI: 10.1161/circresaha.122.321938] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Accepted: 02/23/2023] [Indexed: 03/07/2023]
Abstract
BACKGROUND Removal of circulating plasma low-density lipoprotein cholesterol (LDL-C) by the liver relies on efficient endocytosis and intracellular vesicle trafficking. Increasing the availability of hepatic LDL receptors (LDLRs) remains a major clinical target for reducing LDL-C levels. Here, we describe a novel role for RNF130 (ring finger containing protein 130) in regulating plasma membrane availability of LDLR. METHODS We performed a combination of gain-of-function and loss-of-function experiments to determine the effect of RNF130 on LDL-C and LDLR recycling. We overexpressed RNF130 and a nonfunctional mutant RNF130 in vivo and measured plasma LDL-C and hepatic LDLR protein levels. We performed in vitro ubiquitination assays and immunohistochemical staining to measure levels and cellular distribution of LDLR. We supplement these experiments with 3 separate in vivo models of RNF130 loss-of-function where we disrupted Rnf130 using either ASO (antisense oligonucleotides), germline deletion, or AAV CRISPR (adeno-associated virus clustered regularly interspaced short palindromic repeats) and measured hepatic LDLR and plasma LDL-C. RESULTS We demonstrate that RNF130 is an E3 ubiquitin ligase that ubiquitinates LDLR resulting in redistribution of the receptor away from the plasma membrane. Overexpression of RNF130 decreases hepatic LDLR and increases plasma LDL-C levels. Further, in vitro ubiquitination assays demonstrate RNF130-dependent regulation of LDLR abundance at the plasma membrane. Finally, in vivo disruption of Rnf130 using ASO, germline deletion, or AAV CRISPR results in increased hepatic LDLR abundance and availability and decreased plasma LDL-C levels. CONCLUSIONS Our studies identify RNF130 as a novel posttranslational regulator of LDL-C levels via modulation of LDLR availability, thus providing important insight into the complex regulation of hepatic LDLR protein levels.
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Affiliation(s)
- Bethan L. Clifford
- Department of Medicine, Division of Cardiology, University of California Los Angeles, CA, USA
| | - Kelsey E. Jarrett
- Department of Medicine, Division of Cardiology, University of California Los Angeles, CA, USA
| | - Joan Cheng
- Department of Biological Chemistry, David Geffen School of Medicine at UCLA, University of California Los Angeles, CA, USA
| | - Angela Cheng
- Department of Biological Chemistry, David Geffen School of Medicine at UCLA, University of California Los Angeles, CA, USA
| | - Marcus Seldin
- Department of Biological Chemistry, University of California Irvine, CA, USA
| | - Pauline Morand
- Department of Biological Chemistry, David Geffen School of Medicine at UCLA, University of California Los Angeles, CA, USA
| | | | - Mary Chen
- Edward A. Doisy Department of Biochemistry and Molecular Biology, Saint Louis University, St. Louis, MO, USA
| | - Angel Baldan
- Edward A. Doisy Department of Biochemistry and Molecular Biology, Saint Louis University, St. Louis, MO, USA
| | - Thomas Q. de Aguiar Vallim
- Department of Medicine, Division of Cardiology, University of California Los Angeles, CA, USA
- Department of Biological Chemistry, David Geffen School of Medicine at UCLA, University of California Los Angeles, CA, USA
- Molecular Biology Institute, David Geffen School of Medicine at UCLA, University of California Los Angeles, CA, USA
- Jonsson Comprehensive Cancer Center, David Geffen School of Medicine at UCLA, University of California Los Angeles, CA, USA
| | - Elizabeth J. Tarling
- Department of Medicine, Division of Cardiology, University of California Los Angeles, CA, USA
- Molecular Biology Institute, David Geffen School of Medicine at UCLA, University of California Los Angeles, CA, USA
- Jonsson Comprehensive Cancer Center, David Geffen School of Medicine at UCLA, University of California Los Angeles, CA, USA
- Lead contact
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31
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Hodonsky CJ, Turner AW, Khan MD, Barrientos NB, Methorst R, Ma L, Lopez NG, Mosquera JV, Auguste G, Farber E, Ma WF, Wong D, Onengut-Gumuscu S, Kavousi M, Peyser PA, van der Laan SW, Leeper NJ, Kovacic JC, Björkegren JLM, Miller CL. Integrative multi-ancestry genetic analysis of gene regulation in coronary arteries prioritizes disease risk loci. medRxiv 2023:2023.02.09.23285622. [PMID: 36824883 PMCID: PMC9949190 DOI: 10.1101/2023.02.09.23285622] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/16/2023]
Abstract
Genome-wide association studies (GWAS) have identified hundreds of genetic risk loci for coronary artery disease (CAD). However, non-European populations are underrepresented in GWAS and the causal gene-regulatory mechanisms of these risk loci during atherosclerosis remain unclear. We incorporated local ancestry and haplotype information to identify quantitative trait loci (QTL) for gene expression and splicing in coronary arteries obtained from 138 ancestrally diverse Americans. Of 2,132 eQTL-associated genes (eGenes), 47% were previously unreported in coronary arteries and 19% exhibited cell-type-specific expression. Colocalization analysis with GWAS identified subgroups of eGenes unique to CAD and blood pressure. Fine-mapping highlighted additional eGenes of interest, including TBX20 and IL5 . Splicing (s)QTLs for 1,690 genes were also identified, among which TOR1AIP1 and ULK3 sQTLs demonstrated the importance of evaluating splicing events to accurately identify disease-relevant gene expression. Our work provides the first human coronary artery eQTL resource from a patient sample and exemplifies the necessity of diverse study populations and multi-omic approaches to characterize gene regulation in critical disease processes. Study Design Overview
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32
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Milanese JS, Marcotte R, Costain WJ, Kablar B, Drouin S. Roles of Skeletal Muscle in Development: A Bioinformatics and Systems Biology Overview. Adv Anat Embryol Cell Biol 2023; 236:21-55. [PMID: 37955770 DOI: 10.1007/978-3-031-38215-4_2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/14/2023]
Abstract
The ability to assess various cellular events consequent to perturbations, such as genetic mutations, disease states and therapies, has been recently revolutionized by technological advances in multiple "omics" fields. The resulting deluge of information has enabled and necessitated the development of tools required to both process and interpret the data. While of tremendous value to basic researchers, the amount and complexity of the data has made it extremely difficult to manually draw inference and identify factors key to the study objectives. The challenges of data reduction and interpretation are being met by the development of increasingly complex tools that integrate disparate knowledge bases and synthesize coherent models based on current biological understanding. This chapter presents an example of how genomics data can be integrated with biological network analyses to gain further insight into the developmental consequences of genetic perturbations. State of the art methods for conducting similar studies are discussed along with modern methods used to analyze and interpret the data.
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Affiliation(s)
| | - Richard Marcotte
- Human Health Therapeutics, National Research Council of Canada , Montreal, QC, Canada
| | - Willard J Costain
- Human Health Therapeutics, National Research Council of Canada, Ottawa, ON, Canada
| | - Boris Kablar
- Department of Medical Neuroscience, Anatomy and Pathology, Faculty of Medicine, Dalhousie University, Halifax, NS, Canada
| | - Simon Drouin
- Human Health Therapeutics, National Research Council of Canada , Montreal, QC, Canada.
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Gao B, Li C, Liao Q, Pan T, Ren C, Cao Q. Epicardial fat volume evaluated with multidetector computed tomography and other risk factors for prevalence of three-vessel coronary lesions. Eur J Med Res 2022; 27:308. [PMID: 36572947 PMCID: PMC9793663 DOI: 10.1186/s40001-022-00956-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Accepted: 12/14/2022] [Indexed: 12/28/2022] Open
Abstract
PURPOSE To retrospectively investigate the epicardial fat volume with multidetector computed tomography (MDCT) and other risk factors for the prevalence of three-vessel coronary lesion. MATERIALS AND METHODS MDCT was performed on 424 subjects with or without three-vessel coronary lesion. Blood was tested for triglyceride, high-density lipoprotein (HDL), low-density lipoprotein (LDL), apolipoprotein A (ApoA), apolipoprotein B (ApoB), alanine aminotransferase (ALT), aspartate aminotransferase (AST), lipoprotein a, and fasting blood glucose. RESULTS Among all the subjects, a significant (P < 0.05) negative linear correlation existed between age and ALT or ALT/AST. The epicardial fat had a significant (P < 0.05) negative linear correlation with HDL and Apo A but a positive correlation with age and ApoB/ApoA. The epicardial fat volume and the fasting blood glucose were significantly (P = 0.001) greater in the patients than in the control group, whereas HDL and Apo A were both significantly (P < 0.0001) smaller in the patients than in the control groups. A significant prediction value (P < 0.05) existed in age increase, male gender, epicardial fat increase, low HDL, high LDL, and elevated fasting blood glucose. CONCLUSION Three-vessel coronary lesions are more prevalent in subjects with greater volume of epicardial fat and in male gender.
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Affiliation(s)
- Bulang Gao
- Department of Neurosurgery, Shijiazhuang People’s Hospital, 365 South Jianhua Street, Shijiazhuang, 050011 Hebei China
| | - Caiying Li
- grid.256883.20000 0004 1760 8442Department of Medical Imaging the Second Hospital, Hebei Medical University, Shijiazhuang, 050011 Hebei China
| | - Qibin Liao
- grid.256883.20000 0004 1760 8442Department of Medical Imaging the Second Hospital, Hebei Medical University, Shijiazhuang, 050011 Hebei China
| | - Tong Pan
- grid.256883.20000 0004 1760 8442Department of Medical Imaging the Second Hospital, Hebei Medical University, Shijiazhuang, 050011 Hebei China
| | - Chunfeng Ren
- grid.412633.10000 0004 1799 0733Department of Laboratory Analysis, The First Affiliated Hospital of Zhengzhou University, 1 Longhu Middle Ring Road, Zhengzhou, 450018 Henan China
| | - Qinying Cao
- Department of Neurosurgery, Shijiazhuang People’s Hospital, 365 South Jianhua Street, Shijiazhuang, 050011 Hebei China
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34
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Su C, Xu Z, Shan X, Cai B, Zhao H, Zhang J. Cell-type-specific co-expression inference from single cell RNA-sequencing data. bioRxiv 2022:2022.12.13.520181. [PMID: 36561173 PMCID: PMC9774209 DOI: 10.1101/2022.12.13.520181] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
The inference of gene co-expressions from microarray and RNA-sequencing data has led to rich insights on biological processes and disease mechanisms. However, the bulk samples analyzed in most studies are a mixture of different cell types. As a result, the inferred co-expressions are confounded by varying cell type compositions across samples and only offer an aggregated view of gene regulations that may be distinct across different cell types. The advancement of single cell RNA-sequencing (scRNA-seq) technology has enabled the direct inference of co-expressions in specific cell types, facilitating our understanding of cell-type-specific biological functions. However, the high sequencing depth variations and measurement errors in scRNA-seq data present significant challenges in inferring cell-type-specific gene co-expressions, and these issues have not been adequately addressed in the existing methods. We propose a statistical approach, CS-CORE, for estimating and testing cell-type-specific co-expressions, built on a general expression-measurement model that explicitly accounts for sequencing depth variations and measurement errors in the observed single cell data. Systematic evaluations show that most existing methods suffer from inflated false positives and biased co-expression estimates and clustering analysis, whereas CS-CORE has appropriate false positive control, unbiased co-expression estimates, good statistical power and satisfactory performance in downstream co-expression analysis. When applied to analyze scRNA-seq data from postmortem brain samples from Alzheimer’s disease patients and controls and blood samples from COVID-19 patients and controls, CS-CORE identified cell-type-specific co-expressions and differential co-expressions that were more reproducible and/or more enriched for relevant biological pathways than those inferred from other methods.
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Affiliation(s)
- Chang Su
- Department of Biostatistics, Yale University
| | - Zichun Xu
- Department of Biostatistics, Yale University
| | | | - Biao Cai
- Department of Biostatistics, Yale University
| | - Hongyu Zhao
- Department of Biostatistics, Yale University
| | - Jingfei Zhang
- Information Systems and Operations Management, Emory University
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Su C, Xu Z, Shan X, Cai B, Zhao H, Zhang J. Cell-type-specific co-expression inference from single cell RNA-sequencing data. bioRxiv 2022:2022.12.13.520181. [PMID: 36561173 DOI: 10.1101/2022.04.07.487499] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/26/2023]
Abstract
The inference of gene co-expressions from microarray and RNA-sequencing data has led to rich insights on biological processes and disease mechanisms. However, the bulk samples analyzed in most studies are a mixture of different cell types. As a result, the inferred co-expressions are confounded by varying cell type compositions across samples and only offer an aggregated view of gene regulations that may be distinct across different cell types. The advancement of single cell RNA-sequencing (scRNA-seq) technology has enabled the direct inference of co-expressions in specific cell types, facilitating our understanding of cell-type-specific biological functions. However, the high sequencing depth variations and measurement errors in scRNA-seq data present significant challenges in inferring cell-type-specific gene co-expressions, and these issues have not been adequately addressed in the existing methods. We propose a statistical approach, CS-CORE, for estimating and testing cell-type-specific co-expressions, built on a general expression-measurement model that explicitly accounts for sequencing depth variations and measurement errors in the observed single cell data. Systematic evaluations show that most existing methods suffer from inflated false positives and biased co-expression estimates and clustering analysis, whereas CS-CORE has appropriate false positive control, unbiased co-expression estimates, good statistical power and satisfactory performance in downstream co-expression analysis. When applied to analyze scRNA-seq data from postmortem brain samples from Alzheimer’s disease patients and controls and blood samples from COVID-19 patients and controls, CS-CORE identified cell-type-specific co-expressions and differential co-expressions that were more reproducible and/or more enriched for relevant biological pathways than those inferred from other methods.
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Mauersberger C, Sager HB, Wobst J, Dang TA, Lambrecht L, Koplev S, Stroth M, Bettaga N, Schlossmann J, Wunder F, Friebe A, Björkegren JLM, Dietz L, Maas SL, van der Vorst EPC, Sandner P, Soehnlein O, Schunkert H, Kessler T. Loss of soluble guanylyl cyclase in platelets contributes to atherosclerotic plaque formation and vascular inflammation. Nat Cardiovasc Res 2022; 1:1174-1186. [PMID: 37484062 PMCID: PMC10361702 DOI: 10.1038/s44161-022-00175-w] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Accepted: 10/27/2022] [Indexed: 07/25/2023]
Abstract
Variants in genes encoding the soluble guanylyl cyclase (sGC) in platelets are associated with coronary artery disease (CAD) risk. Here, by using histology, flow cytometry and intravital microscopy, we show that functional loss of sGC in platelets of atherosclerosis-prone Ldlr-/- mice contributes to atherosclerotic plaque formation, particularly via increasing in vivo leukocyte adhesion to atherosclerotic lesions. In vitro experiments revealed that supernatant from activated platelets lacking sGC promotes leukocyte adhesion to endothelial cells (ECs) by activating ECs. Profiling of platelet-released cytokines indicated that reduced platelet angiopoietin-1 release by sGC-depleted platelets, which was validated in isolated human platelets from carriers of GUCY1A1 risk alleles, enhances leukocyte adhesion to ECs. I mp or ta ntly, p ha rm ac ol ogical sGC stimulation increased platelet angiopoietin-1 release in vitro and reduced leukocyte recruitment and atherosclerotic plaque formation in atherosclerosis-prone Ldlr-/- mice. Therefore, pharmacological sGC stimulation might represent a potential therapeutic strategy to prevent and treat CAD.
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Affiliation(s)
- Carina Mauersberger
- German Heart Centre Munich, Department of Cardiology, Technical University of Munich, Munich, Germany
- German Centre for Cardiovascular Research, Munich Heart Alliance, Munich, Germany
- These authors contributed equally: Carina Mauersberger, Hendrik B. Sager
| | - Hendrik B. Sager
- German Heart Centre Munich, Department of Cardiology, Technical University of Munich, Munich, Germany
- German Centre for Cardiovascular Research, Munich Heart Alliance, Munich, Germany
- These authors contributed equally: Carina Mauersberger, Hendrik B. Sager
| | - Jana Wobst
- German Heart Centre Munich, Department of Cardiology, Technical University of Munich, Munich, Germany
- German Centre for Cardiovascular Research, Munich Heart Alliance, Munich, Germany
| | - Tan An Dang
- German Heart Centre Munich, Department of Cardiology, Technical University of Munich, Munich, Germany
- German Centre for Cardiovascular Research, Munich Heart Alliance, Munich, Germany
| | - Laura Lambrecht
- German Heart Centre Munich, Department of Cardiology, Technical University of Munich, Munich, Germany
- German Centre for Cardiovascular Research, Munich Heart Alliance, Munich, Germany
| | - Simon Koplev
- Department of Genetics and Genomic Sciences, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge, UK
| | - Marlène Stroth
- German Heart Centre Munich, Department of Cardiology, Technical University of Munich, Munich, Germany
- German Centre for Cardiovascular Research, Munich Heart Alliance, Munich, Germany
| | - Noomen Bettaga
- German Heart Centre Munich, Department of Cardiology, Technical University of Munich, Munich, Germany
| | - Jens Schlossmann
- Department of Pharmacology and Toxicology, University of Regensburg, Regensburg, Germany
| | - Frank Wunder
- Bayer AG, R&D Pharmaceuticals, Wuppertal, Germany
| | - Andreas Friebe
- Institute of Physiology, Julius Maximilian University of Würzburg, Würzburg, Germany
| | - Johan L. M. Björkegren
- Department of Genetics and Genomic Sciences, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Medicine, Neo, Karolinska Institutet, Karolinska Universitetssjukhuset, Huddinge, Sweden
- Department of Cardiac Surgery and The Heart Clinic, Tartu University Hospital and Department of Cardiology, Institute of Clinical Medicine, Tartu University, Tartu, Estonia
| | - Lisa Dietz
- Bayer AG, R&D Pharmaceuticals, Wuppertal, Germany
| | - Sanne L. Maas
- Institute for Molecular Cardiovascular Research and Interdisciplinary Centre for Clinical Research, Rhine-Westphalia Technical University of Aachen, Aachen, Germany
| | - Emiel P. C. van der Vorst
- Institute for Molecular Cardiovascular Research and Interdisciplinary Centre for Clinical Research, Rhine-Westphalia Technical University of Aachen, Aachen, Germany
- Institute for Cardiovascular Prevention, Ludwig Maximilian University of Munich, Munich, Germany
| | | | - Oliver Soehnlein
- German Centre for Cardiovascular Research, Munich Heart Alliance, Munich, Germany
- Institute for Cardiovascular Prevention, Ludwig Maximilian University of Munich, Munich, Germany
- Institute for Experimental Pathology, University of Münster, Münster, Germany
- Department of Physiology and Pharmacology and Department of Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Heribert Schunkert
- German Heart Centre Munich, Department of Cardiology, Technical University of Munich, Munich, Germany
- German Centre for Cardiovascular Research, Munich Heart Alliance, Munich, Germany
- These authors jointly supervised this work: Heribert Schunkert, Thorsten Kessler
| | - Thorsten Kessler
- German Heart Centre Munich, Department of Cardiology, Technical University of Munich, Munich, Germany
- German Centre for Cardiovascular Research, Munich Heart Alliance, Munich, Germany
- These authors jointly supervised this work: Heribert Schunkert, Thorsten Kessler
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Zhang J, Cheng H, Di Narzo A, Zhu Y, Shan M, Zhang Z, Shao X, Chen J, Wang C, Hao K. Within- and cross-tissue gene regulations were disrupted by PM 2.5 nitrate exposure and associated with respiratory functions. Sci Total Environ 2022; 850:157977. [PMID: 35964746 DOI: 10.1016/j.scitotenv.2022.157977] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/01/2022] [Revised: 07/25/2022] [Accepted: 08/08/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND Pathogenesis of complex diseases often involves multiple organs/tissue-types. To date, the PM2.5 exposure's toxic effects and induced disease risks were not studied at multi-tissue level. METHODS C57BL/6 mice (n = 40) were exposed to PM2.5 NO3- and clean air, respectively, and afterwards assessed respiratory functions and transcriptome in relevant tissues: blood and lung. We constructed within- and cross-tissue gene regulation networks and identified network modules associated with exposure and respiratory functions. RESULTS PM2.5 NO3- exposure elevated naïve B cells proportion in blood (p = 0.0028). Among the 6000 highest expressed genes in blood, 18.8 % (1133 genes) were altered by exposure at p ≤ 0.05 level, among which 763 genes were also associated with respiratory function (enrichment folds = 7.63, p = 2.7E-189). The exposure disrupted blood genes were primarily in the immunoregulation pathways. Both within- and cross-tissue gene network modules were perturbed by exposure and associated with respiratory function. An immunodeficiency related cross-tissue module of 555 genes was affected by exposure (p = 0.0023) and strongly correlated with FEV0.05/FVC (r = 0.61 and p = 3E-5). CONCLUSIONS This study aims to fill in a major knowledge gap and investigated the effect of PM2.5 exposure simultaneously in multiple tissues. We provided novel evidence that PM2.5 NO3- exposure profoundly perturbed within- and cross-tissue gene regulations, and highlighted their roles in the etiology of respiratory decline.
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Affiliation(s)
- Jushan Zhang
- Department of Respiratory Medicine, Shanghai Tenth People's Hospital, Tongji University, Shanghai, China; College of Environmental Science and Engineering, Tongji University, Shanghai, China
| | - Haoxiang Cheng
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Antonio Di Narzo
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Yujie Zhu
- Department of Respiratory Medicine, Shanghai Tenth People's Hospital, Tongji University, Shanghai, China
| | | | - Zhongyang Zhang
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Xiaowen Shao
- Department of Obstetrics and Gynecology, Shanghai Tenth People's Hospital, Tongji University, Shanghai, China
| | - Jia Chen
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Changhui Wang
- Department of Respiratory Medicine, Shanghai Tenth People's Hospital, Tongji University, Shanghai, China
| | - Ke Hao
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Sema4, Stamford, CT, USA.
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Girard D, Vandiedonck C. How dysregulation of the immune system promotes diabetes mellitus and cardiovascular risk complications. Front Cardiovasc Med 2022; 9:991716. [PMID: 36247456 PMCID: PMC9556991 DOI: 10.3389/fcvm.2022.991716] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Accepted: 08/30/2022] [Indexed: 12/15/2022] Open
Abstract
Diabetes mellitus (DM) is a chronic metabolic disorder characterized by persistent hyperglycemia due to insulin resistance or failure to produce insulin. Patients with DM develop microvascular complications that include chronic kidney disease and retinopathy, and macrovascular complications that mainly consist in an accelerated and more severe atherosclerosis compared to the general population, increasing the risk of cardiovascular (CV) events, such as stroke or myocardial infarction by 2- to 4-fold. DM is commonly associated with a low-grade chronic inflammation that is a known causal factor in its development and its complications. Moreover, it is now well-established that inflammation and immune cells play a major role in both atherosclerosis genesis and progression, as well as in CV event occurrence. In this review, after a brief presentation of DM physiopathology and its macrovascular complications, we will describe the immune system dysregulation present in patients with type 1 or type 2 diabetes and discuss its role in DM cardiovascular complications development. More specifically, we will review the metabolic changes and aberrant activation that occur in the immune cells driving the chronic inflammation through cytokine and chemokine secretion, thus promoting atherosclerosis onset and progression in a DM context. Finally, we will discuss how genetics and recent systemic approaches bring new insights into the mechanisms behind these inflammatory dysregulations and pave the way toward precision medicine.
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Affiliation(s)
- Diane Girard
- Université Paris Cité, INSERM UMR-S1151, CNRS UMR-S8253, Institut Necker Enfants Malades, IMMEDIAB Laboratory, Paris, France
- Université Paris Cité, Institut Hors-Mur du Diabète, Faculté de Santé, Paris, France
| | - Claire Vandiedonck
- Université Paris Cité, INSERM UMR-S1151, CNRS UMR-S8253, Institut Necker Enfants Malades, IMMEDIAB Laboratory, Paris, France
- Université Paris Cité, Institut Hors-Mur du Diabète, Faculté de Santé, Paris, France
- *Correspondence: Claire Vandiedonck
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Bauer S, Eigenmann J, Zhao Y, Fleig J, Hawe JS, Pan C, Bongiovanni D, Wengert S, Ma A, Lusis AJ, Kovacic JC, Björkegren JLM, Maegdefessel L, Schunkert H, von Scheidt M. Identification of the Transcription Factor ATF3 as a Direct and Indirect Regulator of the LDLR. Metabolites 2022; 12:metabo12090840. [PMID: 36144244 PMCID: PMC9504235 DOI: 10.3390/metabo12090840] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2022] [Revised: 08/28/2022] [Accepted: 09/02/2022] [Indexed: 11/16/2022] Open
Abstract
Coronary artery disease (CAD) is a complex, multifactorial disease caused, in particular, by inflammation and cholesterol metabolism. At the molecular level, the role of tissue-specific signaling pathways leading to CAD is still largely unexplored. This study relied on two main resources: (1) genes with impact on atherosclerosis/CAD, and (2) liver-specific transcriptome analyses from human and mouse studies. The transcription factor activating transcription factor 3 (ATF3) was identified as a key regulator of a liver network relevant to atherosclerosis and linked to inflammation and cholesterol metabolism. ATF3 was predicted to be a direct and indirect (via MAF BZIP Transcription Factor F (MAFF)) regulator of low-density lipoprotein receptor (LDLR). Chromatin immunoprecipitation DNA sequencing (ChIP-seq) data from human liver cells revealed an ATF3 binding motif in the promoter regions of MAFF and LDLR. siRNA knockdown of ATF3 in human Hep3B liver cells significantly upregulated LDLR expression (p < 0.01). Inflammation induced by lipopolysaccharide (LPS) stimulation resulted in significant upregulation of ATF3 (p < 0.01) and subsequent downregulation of LDLR (p < 0.001). Liver-specific expression data from human CAD patients undergoing coronary artery bypass grafting (CABG) surgery (STARNET) and mouse models (HMDP) confirmed the regulatory role of ATF3 in the homeostasis of cholesterol metabolism. This study suggests that ATF3 might be a promising treatment candidate for lowering LDL cholesterol and reducing cardiovascular risk.
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Affiliation(s)
- Sabine Bauer
- Department of Cardiology, German Heart Centre Munich, Technical University Munich, 80636 Munich, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Munich Heart Alliance, 80802 Munich, Germany
- Correspondence: (S.B.); (M.v.S.); Tel.: +49-(0)89-1218-2367 (S.B.); +49-(0)89-1218-2849 (M.v.S.)
| | - Jana Eigenmann
- Department of Cardiology, German Heart Centre Munich, Technical University Munich, 80636 Munich, Germany
| | - Yuqi Zhao
- Department of Integrative Biology and Physiology, Institute for Quantitative and Computational Biosciences, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
| | - Julia Fleig
- Department of Cardiology, German Heart Centre Munich, Technical University Munich, 80636 Munich, Germany
| | - Johann S. Hawe
- Department of Cardiology, German Heart Centre Munich, Technical University Munich, 80636 Munich, Germany
| | - Calvin Pan
- Departments of Medicine, Human Genetics, Microbiology, Immunology and Molecular Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
| | - Dario Bongiovanni
- DZHK (German Centre for Cardiovascular Research), Partner Site Munich Heart Alliance, 80802 Munich, Germany
- Division of Cardiology, Cardiocentro Ticino Institute, Ente Ospedaliero Cantonale, 6900 Lugano, Switzerland
| | - Simon Wengert
- Helmholtz Pioneer Campus, Helmholtz Center Munich, 85764 Neuherberg, Germany
- Institute of Computational Biology, Helmholtz Center Munich, 85764 Oberschleißheim, Germany
| | - Angela Ma
- Department of Genetics and Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Aldons J. Lusis
- Departments of Medicine, Human Genetics, Microbiology, Immunology and Molecular Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
| | - Jason C. Kovacic
- Victor Chang Cardiac Research Institute, Darlinghurst, Sydney, NSW 2010, Australia
- St. Vincent’s Clinical School, University of New South Wales, Darlinghurst, Sydney, NSW 2010, Australia
- Icahn School of Medicine at Mount Sinai, Cardiovascular Research Institute, New York, NY 10029, USA
| | - Johan L. M. Björkegren
- Department of Genetics and Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Clinical Gene Networks AB, 114 44 Stockholm, Sweden
- Integrated Cardio Metabolic Centre, Karolinska Institutet, Novum, Huddinge, 171 77 Stockholm, Sweden
| | - Lars Maegdefessel
- DZHK (German Centre for Cardiovascular Research), Partner Site Munich Heart Alliance, 80802 Munich, Germany
- Department of Vascular and Endovascular Surgery, Klinikum Rechts der Isar, Technical University Munich, 81675 Munich, Germany
- Department of Molecular Medicine and Surgery, Karolinska Institutet, 171 76 Stockholm, Sweden
| | - Heribert Schunkert
- Department of Cardiology, German Heart Centre Munich, Technical University Munich, 80636 Munich, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Munich Heart Alliance, 80802 Munich, Germany
| | - Moritz von Scheidt
- Department of Cardiology, German Heart Centre Munich, Technical University Munich, 80636 Munich, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Munich Heart Alliance, 80802 Munich, Germany
- Correspondence: (S.B.); (M.v.S.); Tel.: +49-(0)89-1218-2367 (S.B.); +49-(0)89-1218-2849 (M.v.S.)
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Ma L, Bryce NS, Turner AW, Di Narzo AF, Rahman K, Xu Y, Ermel R, Sukhavasi K, d’Escamard V, Chandel N, V’Gangula B, Wolhuter K, Kadian-Dodov D, Franzen O, Ruusalepp A, Hao K, Miller CL, Björkegren JLM, Kovacic JC. The HDAC9-associated risk locus promotes coronary artery disease by governing TWIST1. PLoS Genet 2022; 18:e1010261. [PMID: 35714152 PMCID: PMC9246173 DOI: 10.1371/journal.pgen.1010261] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Revised: 06/30/2022] [Accepted: 05/17/2022] [Indexed: 11/18/2022] Open
Abstract
Genome wide association studies (GWAS) have identified thousands of single nucleotide polymorphisms (SNPs) associated with the risk of common disorders. However, since the large majority of these risk SNPs reside outside gene-coding regions, GWAS generally provide no information about causal mechanisms regarding the specific gene(s) that are affected or the tissue(s) in which these candidate gene(s) exert their effect. The ‘gold standard’ method for understanding causal genes and their mechanisms of action are laborious basic science studies often involving sophisticated knockin or knockout mouse lines, however, these types of studies are impractical as a high-throughput means to understand the many risk variants that cause complex diseases like coronary artery disease (CAD). As a solution, we developed a streamlined, data-driven informatics pipeline to gain mechanistic insights on complex genetic loci. The pipeline begins by understanding the SNPs in a given locus in terms of their relative location and linkage disequilibrium relationships, and then identifies nearby expression quantitative trait loci (eQTLs) to determine their relative independence and the likely tissues that mediate their disease-causal effects. The pipeline then seeks to understand associations with other disease-relevant genes, disease sub-phenotypes, potential causality (Mendelian randomization), and the regulatory and functional involvement of these genes in gene regulatory co-expression networks (GRNs). Here, we applied this pipeline to understand a cluster of SNPs associated with CAD within and immediately adjacent to the gene encoding HDAC9. Our pipeline demonstrated, and validated, that this locus is causal for CAD by modulation of TWIST1 expression levels in the arterial wall, and by also governing a GRN related to metabolic function in skeletal muscle. Our results reconciled numerous prior studies, and also provided clear evidence that this locus does not govern HDAC9 expression, structure or function. This pipeline should be considered as a powerful and efficient way to understand GWAS risk loci in a manner that better reflects the highly complex nature of genetic risk associated with common disorders.
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Affiliation(s)
- Lijiang Ma
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- Cardiovascular Research Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Nicole S. Bryce
- Victor Chang Cardiac Research Institute, Darlinghurst, Australia; St Vincent’s Clinical School, University of NSW, Sydney, Australia
| | - Adam W. Turner
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia School of Medicine, Charlottesville, Virginia, Unites States of America
| | - Antonio F. Di Narzo
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Karishma Rahman
- Cardiovascular Research Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Yang Xu
- Cardiovascular Research Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Raili Ermel
- Department of Cardiac Surgery and The Heart Clinic, Tartu University Hospital, Tartu, Estonia
| | - Katyayani Sukhavasi
- Department of Cardiac Surgery and The Heart Clinic, Tartu University Hospital, Tartu, Estonia
| | - Valentina d’Escamard
- Cardiovascular Research Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Nirupama Chandel
- Cardiovascular Research Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Bhargavi V’Gangula
- Cardiovascular Research Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Kathryn Wolhuter
- Victor Chang Cardiac Research Institute, Darlinghurst, Australia; St Vincent’s Clinical School, University of NSW, Sydney, Australia
| | - Daniella Kadian-Dodov
- Zena and Michael A. Wiener Cardiovascular Institute and Marie-Josée and Henry R, Kravis Center for Cardiovascular Health Icahn School of Medicine at Mount Sinai, New York, New York, Unites States of America
| | - Oscar Franzen
- Integrated Cardio Metabolic Centre, Department of Medicine, Karolinska Institutet, Karolinska Universitetssjukhuset, Huddinge, Sweden
| | - Arno Ruusalepp
- Department of Cardiac Surgery and The Heart Clinic, Tartu University Hospital, Tartu, Estonia
| | - Ke Hao
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- Department of Respiratory Medicine, Shanghai Tenth People’s Hospital, Tongji University, Shanghai, China
| | - Clint L. Miller
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia School of Medicine, Charlottesville, Virginia, Unites States of America
| | - Johan L. M. Björkegren
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- Integrated Cardio Metabolic Centre, Department of Medicine, Karolinska Institutet, Karolinska Universitetssjukhuset, Huddinge, Sweden
| | - Jason C. Kovacic
- Cardiovascular Research Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- Victor Chang Cardiac Research Institute, Darlinghurst, Australia; St Vincent’s Clinical School, University of NSW, Sydney, Australia
- Zena and Michael A. Wiener Cardiovascular Institute and Marie-Josée and Henry R, Kravis Center for Cardiovascular Health Icahn School of Medicine at Mount Sinai, New York, New York, Unites States of America
- * E-mail:
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Sonawane AR, Aikawa E, Aikawa M. Connections for Matters of the Heart: Network Medicine in Cardiovascular Diseases. Front Cardiovasc Med 2022; 9:873582. [PMID: 35665246 PMCID: PMC9160390 DOI: 10.3389/fcvm.2022.873582] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Accepted: 04/19/2022] [Indexed: 01/18/2023] Open
Abstract
Cardiovascular diseases (CVD) are diverse disorders affecting the heart and vasculature in millions of people worldwide. Like other fields, CVD research has benefitted from the deluge of multiomics biomedical data. Current CVD research focuses on disease etiologies and mechanisms, identifying disease biomarkers, developing appropriate therapies and drugs, and stratifying patients into correct disease endotypes. Systems biology offers an alternative to traditional reductionist approaches and provides impetus for a comprehensive outlook toward diseases. As a focus area, network medicine specifically aids the translational aspect of in silico research. This review discusses the approach of network medicine and its application to CVD research.
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Affiliation(s)
- Abhijeet Rajendra Sonawane
- Center for Interdisciplinary Cardiovascular Sciences, Division of Cardiovascular Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
- Center for Excellence in Vascular Biology, Division of Cardiovascular Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
| | - Elena Aikawa
- Center for Interdisciplinary Cardiovascular Sciences, Division of Cardiovascular Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
- Center for Excellence in Vascular Biology, Division of Cardiovascular Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
| | - Masanori Aikawa
- Center for Interdisciplinary Cardiovascular Sciences, Division of Cardiovascular Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
- Center for Excellence in Vascular Biology, Division of Cardiovascular Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
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Abstract
Atherosclerosis is an inflammatory disease of the large arteries that is the major cause of cardiovascular disease (CVD) and stroke. Here, we review the current understanding of the molecular, cellular, genetic, and environmental contributions to atherosclerosis, from both individual pathway and systems perspectives. We place an emphasis on recent developments, some of which have yielded unexpected biology, including previously unknown heterogeneity of inflammatory and smooth muscle cells in atherosclerotic lesions, roles for senescence and clonal hematopoiesis, and links to the gut microbiome.
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Affiliation(s)
- Johan L M Björkegren
- Department of Genetics and Genomic Sciences, Division of Cardiology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Medicine, Huddinge, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden.
| | - Aldons J Lusis
- Department of Medicine/Division of Cardiology, Department of Microbiology, Immunology and Molecular Genetics, Department of Human Genetics, A2-237 Center for the Health Sciences, University of California, Los Angeles, Los Angeles, CA USA.
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Bardin M, Pawelzik SC, Lagrange J, Mahdi A, Arnardottir H, Regnault V, Fève B, Lacolley P, Michel JB, Mercier N, Bäck M. The resolvin D2 - GPR18 axis is expressed in human coronary atherosclerosis and transduces atheroprotection in apolipoprotein E deficient mice. Biochem Pharmacol 2022; 201:115075. [PMID: 35525326 DOI: 10.1016/j.bcp.2022.115075] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2022] [Revised: 04/28/2022] [Accepted: 04/29/2022] [Indexed: 01/17/2023]
Abstract
Chronic inflammation in atherosclerosis reflects a failure in the resolution of inflammation. Pro-resolving lipid mediators derived from omega-3 fatty acids reduce the development of atherosclerosis in murine models. The aim of the present study was to decipher the role of the specialized proresolving mediator (SPM) resolvin D2 (RvD2) in atherosclerosis and its signaling through the G-protein coupled receptor (GPR) 18. The ligand and receptor were detected in human coronary arteries in relation to the presence of atherosclerotic lesions and its cellular components. Importantly, RvD2 levels were significantly higher in atherosclerotic compared with healthy human coronary arteries. Furthermore, apolipoprotein E (ApoE) deficient hyperlipidemic mice were treated with either RvD2 or vehicle in the absence and presence of the GPR18 antagonist O-1918. RvD2 significantly reduced atherosclerosis, necrotic core, and pro-inflammatory macrophage marker expression. RvD2 in addition enhanced macrophage phagocytosis. The beneficial effects of RvD2 were not observed in the presence of O-1918. Taken together, these results provide evidence of atheroprotective pro-resolving signalling through the RvD2-GPR18 axis.
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Affiliation(s)
| | - Sven-Christian Pawelzik
- Department of Medicine Solna, Karolinska Institutet and Department of Cardiology, Karolinska University Hospital, Stockholm, Sweden
| | - Jeremy Lagrange
- Université de Lorraine, Inserm, DCAC, Nancy, France; CHRU Nancy, Vandœuvre-lès-Nancy, France
| | - Ali Mahdi
- Department of Medicine Solna, Karolinska Institutet and Department of Cardiology, Karolinska University Hospital, Stockholm, Sweden
| | - Hildur Arnardottir
- Department of Medicine Solna, Karolinska Institutet and Department of Cardiology, Karolinska University Hospital, Stockholm, Sweden
| | | | - Bruno Fève
- INSERM UMR_S938, Centre de recherche Saint-Antoine, Institut Hospitalo-Universitaire, Université de la Sorbonne, ICAN, 75012 Paris, France
| | | | | | | | - Magnus Bäck
- Université de Lorraine, Inserm, DCAC, Nancy, France; Department of Medicine Solna, Karolinska Institutet and Department of Cardiology, Karolinska University Hospital, Stockholm, Sweden.
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Bankier S, Michoel T. eQTLs as causal instruments for the reconstruction of hormone linked gene networks. Front Endocrinol (Lausanne) 2022; 13:949061. [PMID: 36060942 PMCID: PMC9428692 DOI: 10.3389/fendo.2022.949061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Accepted: 07/25/2022] [Indexed: 11/17/2022] Open
Abstract
Hormones act within in highly dynamic systems and much of the phenotypic response to variation in hormone levels is mediated by changes in gene expression. The increase in the number and power of large genetic association studies has led to the identification of hormone linked genetic variants. However, the biological mechanisms underpinning the majority of these loci are poorly understood. The advent of affordable, high throughput next generation sequencing and readily available transcriptomic databases has shown that many of these genetic variants also associate with variation in gene expression levels as expression Quantitative Trait Loci (eQTLs). In addition to further dissecting complex genetic variation, eQTLs have been applied as tools for causal inference. Many hormone networks are driven by transcription factors, and many of these genes can be linked to eQTLs. In this mini-review, we demonstrate how causal inference and gene networks can be used to describe the impact of hormone linked genetic variation upon the transcriptome within an endocrinology context.
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